Radar based system and method for detection of an object and generation of plots holding radial velocity data, and system for detection and classification of unmanned aerial vehicles, UAVs

ABSTRACT

A Frequency Modulated Continuous Wave, FMCW, radar system that includes one or more antennas configured to transmit and receive FMCW radar wave signals for scanning for objects within a full circular detection coverage range, and processing circuitry configured to provide scan data based on transmitted and received FMCW radar signals and azimuth position of the antenna(s). The processing circuitry is configured to generate first type radar plots that holds range, radial velocity and return energy data for one or more detected objects, and second type radar plots that holds azimuth, range and return energy data for one or more detected objects. The processing circuitry is also configured to generate full data type radar plots by combining first and second type radar plots having corresponding range data, whereby each full data type radar plot holds azimuth, range, radial velocity and return energy data for one or more detected objects.

TECHNICAL FIELD

The disclosure relates to a radar based system and method using aFrequency Modulated Continuous Wave, FMCW, radar system for scanning anddetection of objects, and more particularly to generation of plotsholding radial velocity data. The generated plots can be used fortracking and classification of detected objects, including objects suchas Unmanned Aerial Vehicles, UAVs.

The disclosure further relates to a system for detection andclassification of Unmanned Aerial Vehicles, UAVs. The classification ofthe UAVs may be used to make a distinction between several detectedUAVs.

BACKGROUND

In recent years the number of small Unmanned Aerial Vehicles, UAVs,available to civilian users has largely increased. These platforms maybe privately used for leisure and filming, but also for applicationssuch as agriculture and environmental monitoring, surveillance, anddisaster response. However, small UAVs can also be misused to performanti-social, unsafe, and even criminal actions, such as privacyviolation, collision hazard (with people, other UAVs, and largeraircraft), and even transport of illicit materials. As a result, thereis an increasing interest in developing sensor systems that can detectand track UAVs. Detection and tracking of AUVs with radar posessignificant challenges, as small UAVs typically have a low radar crosssection and fly at lower speed and altitude in comparison withconventional aircrafts. Small UAVs are also capable of highly variedmotion, which complicates the task of separating them from clutterstationary background. Also the high maneuverability of small UAVs makesthe tracking problem more difficult, as it is not possible to makestrong assumptions about the expected UAV motion.

FMCW radar systems are well-known and wide spread for use in theautomotive sector and other industrial applications, where the FMCWradar system provides range and Doppler information of a detected objector target, where the Doppler frequency shift may be transformed into theradial velocity of the detected object or target.

During the operation of an FMCW radar, the system transmits a continuousradio energy with a frequency modulated by a triangular orsawtooth-shaped signal. As a result, the frequency of the transmittedsignal varies gradually with time. When the signal is reflected by anobject, the received waveform will build up a delayed replica of thetransmitted waveform, with the time delay as a measure of the targetrange. If the target is moving, the radar system will register a Dopplershift within the received signal. Compared to the frequency of theemitted signal, the received signal will show a higher frequency whenthe target is approaching and a lower frequency when the target ismoving away from the radar location. Thus, the total Doppler shift mayresult from the superposition of both source and observer motions.Specifically, the amount of Doppler shift is directly proportional tothe radial speed of the target.

In range-Doppler processing, range and velocity information of movingobjects is retrieved by applying a double Fourier transform to thereceived signal. The first transform (range FFT) is applied to thereceived signal from a transmitted upsweep in order to produce a highresolution range line. The range FFT is repeated for a chosenintegration time to obtain an appropriate number of range lines, and thesecond Fourier transform (Doppler FFT) is now applied across theobtained number of range lines. The result is a so-called range-Dopplermap, or range-radial velocity map, where one axis represents range andthe other axis represents radial velocity. The range-Doppler map is amatrix of range-velocity cells holding return signal values of targetsbeing hit, where the amplitude value of a range-velocity cell representsthe return energy of the transmitted radar wave signal being transmittedfrom a target having the range and radial velocity indicated by theposition of the range-velocity cell.

The range-Doppler map or matrix may be arranged with a number individualtarget ranges along the x-axis and a number of individual velocityranges along the y-axis, whereby a column of the matrix represents thevelocity detection span for a given individual target range, and a rowrepresents the range detection span for a given individual targetvelocity range. For a given individual target range, several differenttarget velocities with different return signal values may be observed,where the observed radial velocities and return signal values arerepresented by the data of the velocity column corresponding to theindividual target range. The velocity column may be referred to as aso-called Doppler signature, and the range-Doppler map/matrix thenconsists of the Doppler signatures of all the individual target ranges.For a given target range, the data of the corresponding Dopplersignature varies with time, and when successive Doppler signatures areobtained for the same target range, such as by generating a number ofsuccessive range-Doppler maps/matrixes, these Doppler signatures may beconcatenated into a so-called Doppler spectrogram, showing the Dopplerfrequencies or radial velocities as a function of time for theindividual target range being observed.

High range resolution FMCW radar systems are now also being used fordetecting and characterizing small UAVs by using micro-Doppler analysisof obtained range-Doppler data. The relative motion of parts ischaracteristic for different classes of targets, e.g. the flappingmotion of a bird's wing vs. the spinning of propeller blades. In arange-Doppler map or range-radial velocity map, the moving parts of abody causes a characteristic Doppler signature, where the maincontribution comes from the torso of the body, which causes the Dopplerfrequency of the target, while the flapping motion of bird wings orpropeller blades induces modulation on the returned radar signal andgenerates sidebands around the central Doppler frequency of a Dopplersignature, which may be referred to as micro-Doppler signatures. Thewidth of the sidebands of a micro-Doppler signature within arange-Doppler map/matrix may therefore be indicative of the type oftarget being hit by the transmitted radar waves. When using radialvelocity for a range-Doppler map, the width of the sidebands of amicro-Doppler signature will then be given by the width of the radialvelocity span of the micro-Doppler signature.

In order to generate a track for a target, a number of matching plotshave to be generated, where a plot holds range, azimuth, amplitude andradial velocity information of a validated target. Furthermore, the FMCWradar system may have to scan for objects within a full circular rangeof 360° at a high repetition frequency, which requires a high number ofrather complicated signal processing steps, especially for generation ofthe radial velocity information, to be performed within a limited timeand with limited processing power.

Today's FMCW radar systems incorporates signal processors, which performclutter filtering of the returned radar wave signals, calculaterange-Doppler maps to obtain range, amplitude and radial velocityinformation of a validated target, which are then combined with azimuthinformation, from where the combined information is processed by a plotprocessor to obtain plots of the validated target. For FMCW radarsystems scanning for objects within a full circular range of 360°, scandata may be obtained with reference to a so-called radar image, which isdivided in a number image lines, which again is divided in a number ofrange cells, where each image line covers a given azimuth range, andwith the total number of image lines covering a full circular azimuthrange of from 0° to 360°.

For each image line holding a specific number of range cells andcovering a specific azimuth range, a sequence of signals is transmittedwithin a timeframe of which the radar system covers the azimuth range ofthe image line, and a sequence of return signal is obtained, whichreturn signals may be transformed into a range-Doppler map. Data fromthe range-Doppler map may be combined with the azimuth angle of thecorresponding image line, to obtain a full data set holding range,azimuth, amplitude and radial velocity information of a validatedtarget. A plot for a target may be generated based on a number ofneighboring range cells having matching azimuth and radial velocitydata, and may hold range cells within the same image line and withinseveral neighboring image lines.

Thus, a plot may be generated based on information from severalconsecutively arranged image lines covering several azimuth ranges, andusually data are obtained for a group including all the image lines of afull circular azimuth range of from 0° to 360° before calculations arestarted for defining plots of detected targets. The quality of a plot ishighly dependent on the number of return signals received by the radarsystem within a certain time period, and therefore depends on the numberof transmitted signals within the timeframe of an image line, and alsoon the repetition frequency of the scanning FMCW radar system. A majorlimiting factor in using a high number of transmitted signals and a highscanning repetition frequency is the high requirements to signalprocessing speed and power.

The quality of the detection and tracking performance of the radarsystem highly relates to the quality of the generated plot data, andthereby to the speed at which the plot data can be generated. Thus,there is a need for improved techniques of processing received radarscan signals in order to provide high quality plot data, which can beused for tracking and classification of detected objects, includingobjects such as Unmanned Aerial Vehicles, UAVs. There is also a need forimproved techniques for generating radar plots based on received radarscan signals, and for generating object tracks, including UnmannedAerial Vehicle, UAV, tracks, based on radar plots obtained from receivedradar scan signals. There is also a need for improved techniques forclassification of generated object tracks to thereby identify tracksrepresenting real Unmanned Aerial Vehicles, UAVs.

A UAV can be a known or co-operating UAV, but a UAV can also be anunknown or non co-operating UAV, such as a hostile UAV. The flight pathof a known or co-operating UAV may be controlled from a control stationby exchange of telemetric data, while there is no exchange of telemetricdata with an unknown or non co-operating UAV, and therefore no controlof the flight path of the non co-operating UAV.

Known UAV sensor systems include radar detection systems, where theradar detection system may comprise a Doppler type radar, such as aFrequency Modulated Continuous Wave, FMCW, radar. However, such radardetection systems are not able to make a distinction between a known orunknown UAV.

Thus, there is a need for an improved sensor system, which can trackUAVs and make a distinction between a known and controlled UAV and anunknown and un-controlled UAV.

SUMMARY

The aspects of the disclosed embodiments are directed to providing asystem and a method, which can generate full data type radar plotsholding range, azimuth, amplitude and radial velocity information of avalidated target within a limited time, thereby allowing for a highscanning frequency, and a higher accuracy of tracks generated based onthe plot data.

According to a first aspect there is provided a Frequency ModulatedContinuous Wave, FMCW, radar system comprising: one or more antennasconfigured to transmit and receive FMCW radar wave signals for scanningfor objects within a full circular detection coverage range; and

processing circuitry configured to provide scan data based ontransmitted and received FMCW radar signals and azimuth position of theantenna(s), and to generate radar plots based on obtained scan data;wherein

the processing circuitry is configured to:

provide scan data representing range cells within image lines ofcircular radar images, where each radar image holds a number of imagelines defining a full circular radar image, with each image linecorresponding to an azimuth orientation, and where each image line holdsa number of range cells, with each range cell corresponding to adistance to the radar antenna(s), and wherein an object, which isdetected within an azimuth orientation and range to the radarantenna(s), is represented by a number of hit range cells in one or moreimage lines, and wherein each hit range cell holds data for energy ofreturned signal(s) and data for radial velocity or velocities based onDoppler frequency signals, said scan data thereby for each hit rangecell holding information of range, azimuth orientation, energy ofreturned radar wave signals, and radial velocity or velocities of adetected object;and whereinthe processing circuitry is further configured to:generate first type radar plots for detected objects based on obtainedscan data, where each first type radar plot is based on data from anumber of neighboring hit range cells within one or more image lines ofa first full circular radar image, each said first type radar plotholding range, radial velocity and return energy data for one or moredetected objects;generate second type radar plots for detected objects based on obtainedscan data, where each second type radar plot is based on data from anumber of neighboring hit range cells within one or more image lines ofsaid first full circular radar image, each said second type radar plotholding azimuth, range and return energy data for one or more detectedobjects; andgenerate full data type radar plots by combining first and second typeradar plots having corresponding range data, each said full data typeradar plot thereby holding azimuth, range, radial velocity and returnenergy data for one or more detected objects.

By dividing the process of generating data for the full data type radarplots into several steps, the use of processing power is optimized, andthe final plot data can be obtained within a very short time. Thisallows a high scanning rate, which again improves the quality of thefinal plot data and a higher accuracy of tracks generated based on theplot data.

In a possible implementation form of the first aspect, the processingcircuitry is configured to generate first type radar plots based ongrouping of neighboring hit range cells within one or more image linesof said first full circular radar image having matching range and radialvelocity data, and

generate second type radar plots based on grouping of neighboring hitrange cells within one or more image lines of said first full circularradar image having matching range and azimuth data.

In a possible implementation form of the first aspect, the processingcircuitry is configured to initiate the generation of the first typeradar plots before initiating the generation of the second type radarplots.

The generation of the radial velocity data, which may be based ongeneration of range-Doppler maps, is the most computational powerconsuming process of the computational processes required for generationof data for full data type radar plots, while generation of azimuth andrange data requires less computational power. In order to obtain fulldata type radar plots for a full circular radar scan, scan data need tobe provided and analyzed for a full circular radar image. By initiatingthe generation of the first type radar plots, and thereby the generationof the radial velocity data, before initiating the generation of thesecond type radar plots, which holds azimuth and range data, the totalcomputational time needed to obtain plots holding data for all imagelines of a circular radar image can be reduced.

In a possible implementation form of the first aspect, the processingcircuitry is configured to initiate the generation of the first typeradar plots upon obtaining scan data for range cells of a first imageline of said first full circular radar image.

In a possible implementation form of the first aspect, the processingcircuitry is configured to generate the first type radar plots byanalyzing range and radial velocity data received for the hit rangecells, if any, of the first image line of said first full circular radarimage, and by grouping neighboring hit range cells having matching rangeand radial velocity data into a number of corresponding first type rangeradar plots, if there is any match.

In a possible implementation form of the first aspect, the processingcircuitry is configured to continue generation of the first type radarplots upon obtaining scan data for range cells of a next image line ofsaid first full circular radar image; and

continue generation of the first type radar plots until scan data hasbeen obtained for all image line of said first full circular radarimage, thereby obtaining first type radar plots for said first fullcircular radar image, each said first type radar plot holding range,radial velocity and return energy data for one or more detected objects.

In a possible implementation form of the first aspect, the processingcircuitry is configured to continue the generation of the first typeradar plot by analyzing range and radial velocity data obtained for hitrange cells of the different image lines, and by grouping neighboringhit range cells having matching range and radial velocity data into anumber of corresponding first type range radar plots.

In a possible implementation form of the first aspect, the processingcircuitry is configured to initiate the generation of the second typeradar plots when having obtained scan data for all image lines withinsaid first full circular radar image.

In a possible implementation form of the first aspect, the processingcircuitry is configured to generate the second type radar plots byanalyzing range and azimuth data received for the hit range cells ofimage lines of a full circular radar image, and by grouping neighboringhit range cells having matching range and azimuth data into a number ofcorresponding second type range radar plots, thereby obtaining secondtype radar plots for the full circular radar image, each second typeradar plot holding azimuth, range and return energy data for one or moredetected objects.

In a possible implementation form of the first aspect, the processingcircuitry is configured to generate the full data type radar plots forsaid first full circular radar image by comparing range data of theobtained first and second type radar plots of the full circular radarimage, and by combining first and second type radar plots havingmatching range data into corresponding full data type radar plots, eachsaid full data type radar plot thereby holding azimuth, range, radialvelocity and return energy data for one or more detected objects.

In a possible implementation form of the first aspect, the processingcircuitry is configured to select irregular type radar plots from fulldata type radar plots having velocity data representing both positiveand negative radial velocities.

In a possible implementation form of the first aspect, the processingcircuitry is configured to select a full data type radar plot as anirregular type radar plot when the velocity data of the full data typeradar plot represents positive and negative radial velocities with atleast a predetermined minimum velocity difference between the mostpositive radial velocity and the most negative radial velocity.

In a possible implementation form of the first aspect, the processingcircuitry is configured to select a full data type radar plot as aregular type radar plot when the velocity data of the full data typeradar plot represents positive radial velocities only.

In a possible implementation form of the first aspect, the processingcircuitry is configured to select a full data type radar plot as aregular type radar plot when the velocity data of the full data typeradar plot represents positive and negative radial velocities with atmaximum velocity difference between the most positive radial velocityand the most negative radial velocity being less than said predeterminedminimum velocity difference.

In a possible implementation form of the first aspect, the system isconfigured to provide scan data indicative of radial velocities within apredetermined positive velocity range and a predetermined negativevelocity range of same size as the predetermined positive velocityrange. The predetermined minimum velocity difference between the mostpositive radial velocity and the most negative radial velocity may be atleast 50%, such as at least 60%, such as at least 70%, or such as atleast 75% of the combined predetermined positive and negative velocityranges.

In a possible implementation form of the first aspect, the system isconfigured to provide scan data indicative of radial velocities withinthe range of −30 to +30 m/s. In a possible implementation form of thefirst aspect, the predetermined minimum velocity difference between themost positive radial velocity and the most negative radial velocity isat least 45 m/s.

In a possible implementation form of the first aspect, the processingcircuitry is configured to generate one or more unmanned aerial vehicle,UAV, tracks, where each UAV track is based on at least two irregulartype radar plots having a match between corresponding data of said atleast two irregular type radar plots. Here, in a possible implementationform of the first aspect, the match between corresponding data ofirregular type radar plots comprises a match between radial velocitydata. In a possible implementation form of the first aspect, the matchbetween corresponding data of irregular type radar plots comprises amatch between range data. In a possible implementation form of the firstaspect, the match between corresponding data of irregular type radarplots comprises a match between return energy data.

In a possible implementation form of the first aspect, the processingcircuitry is configured to select an irregular type radar plot as adiscarded irregular type radar plot, when the irregular type radar plotdoes not have a match with any irregular type radar plots.

In a possible implementation form of the first aspect, the processingcircuitry is configured to generate one or more bird tracks, where eachbird track is based on a match between corresponding data of at leasttwo, three or four regular type radar plots and/or second type radarplots having no match with a first type radar plot. In a possibleimplementation form of the first aspect, the match between correspondingdata of regular type radar plots and/or second type radar plotscomprises a match between range data. In a possible implementation formof the first aspect, the match between corresponding data of regulartype radar plots and/or second type radar plots comprises a matchbetween radial velocity data. In a possible implementation form of thefirst aspect, the match between corresponding data of regular type radarplots and/or second type radar plots comprises a match between returnenergy data.

In a possible implementation form of the first aspect, the processingcircuitry is configured to determine if there is a match between data ofa discarded irregular type radar plot and corresponding data of agenerated bird track, and to include the discarded plot into said birdtrack if there is a match, and if there is no match, then to classifythe discarded plot as representing a “hovering vehicle” track.

In a possible implementation form of the first aspect, the processingcircuitry is configured to determine for the plots of a generated UAVtrack:

an outer energy sum being the sum of return energies for range cellsrepresenting positive and negative radial velocity signals within outervelocity ranges of the observed radial velocity range; and

a center energy sum being the sum of return energies for range cellsrepresenting radial velocity signals within a center range of theobserved radial velocity range, and/or a total energy sum being thetotal sum of return energies of range cells representing all radialvelocity signals of the observed radial velocity range.

In a possible implementation form of the first aspect, the processingcircuitry is further configured to classify the UAV track as a real UAVtrack or non-real UAV track based at least partly on a comparison of thedetermined outer energy sum with the determined center energy sum orwith the determined total energy sum. In a possible implementation formof the first aspect, the processing circuitry is configured to classifythe UAV track as a real UAV track or non-real UAV track based at leastpartly on a comparison of the determined total energy sum with apredetermined maximum energy representing a predetermined maximum radarcross-section.

In a possible implementation form of the first aspect, the processingcircuitry is configured to update a generated bird track with newregular type radar plots and/or second type radar plots having no matchwith a first type radar plot,

determine for said updated bird rack, a sum of return energies from thereturn energy data being hold by the radar plots representing said birdtrack,

determine velocity, acceleration, direction and sinuosity of movementcurve from changing track data of said updated bird track, and

classify the bird track as a small bird track, a medium bird track, alarge bird track, a flock of bird track, or as a non-bird track, basedon the determined sum of return energies, and based on the determinedvelocity, acceleration, direction and sinuosity of movement curve.

In a possible implementation form of the first aspect, the processingcircuitry is configured to forward, in real time, data representing theclassified tracks to a display unit, said display unit being configuredfor displaying classified tracks based on the received track data. In apossible implementation form of the first aspect, the processingcircuitry is configured to forward data representing the classifiedtracks to a storage unit, said storage unit being configured for storingthe classified track data.

According to the first aspect, there is also provided a method ofgenerating radar plots including radial velocity data, said method usinga Frequency Modulated Continuous Wave, FMCW, radar system holding one ormore antennas configured to transmit and receive FMCW radar wave signalsfor scanning for objects within a full circular detection coveragerange, and holding processing circuitry, which is configured to obtainscan data based on transmitted and received FMCW radar signals andazimuth position of the antenna(s), and which is configured to generateradar plots based on obtained scan data; wherein the method comprises:

obtaining scan data representing range cells within image lines ofcircular radar images, where each radar image holds a number of imagelines defining a full circular radar image, with each image linecorresponding to an azimuth orientation, and where each image line holdsa number of range cells, with each range cell corresponding to adistance to the radar antenna(s), and wherein an object, which isdetected within an azimuth orientation and range to the radarantenna(s), is represented by a number of hit range cells in one or moreimage lines, and wherein each hit range cell holds data for energy ofreturned signal(s) and data for radial velocity or velocities based onDoppler frequency signals, said scan data thereby for each hit rangecell holding information of range, azimuth orientation, energy ofreturned radar wave signals, and radial velocity or velocities of adetected object; and wherein the method further comprises:generating first type radar plots for detected objects based on obtainedscan data, where each first type radar plot is based on data from anumber of neighboring hit range cells within one or more image lines ofa first full circular radar image, each said first type radar plotholding range, radial velocity and return energy data for one or moredetected objects;generating second type radar plots for detected objects based onobtained scan data, where each second type radar plot is based on datafrom a number of neighboring hit range cells within one or more imagelines of said first full circular radar image, each said second typeradar plot holding azimuth, range and return energy data for one or moredetected objects; andgenerating full data type radar plots by combining first and second typeradar plots having corresponding range data, each said full data typeradar plot thereby holding azimuth, range, radial velocity and returnenergy data for one or more detected objects.

In a possible implementation form of the method of the first aspect, thegeneration of the first type radar plots is based on grouping ofneighboring hit range cells within one or more image lines of said firstfull circular radar image having matching range and radial velocitydata, and the generation of the second type radar plots is based ongrouping of neighboring hit range cells within one or more image linesof said first full circular radar image having matching range andazimuth data.

In a possible implementation form of the method of the first aspect, thegeneration of the first type radar plots is initiated before initiatingthe generation of the second type radar plots.

In a possible implementation form of the method of the first aspect, thegeneration of the first type radar plots is initiated when scan data forrange cells of a first image line of a first full circular radar imageis obtained.

In a possible implementation form of the method of the first aspect, thestep of generating the first type radar plots comprises:

analyzing range and radial velocity data obtained for the hit rangecells, if any, of the first image line, and

grouping neighboring hit range cells having matching range and radialvelocity data into a number of corresponding first type range radarplots, if there is any match.

In a possible implementation form of the method of the first aspect, thestep of generating the first type radar plots further comprises:

continue generation of the first type radar plots upon obtaining scandata for range cells of a next image line of said first full circularradar image; and

continue generation of the first type radar plots until scan data hasbeen obtained for all image line of said first full circular radarimage, thereby obtaining first type radar plots for a first fullcircular radar image, each said first type radar plot holding range,radial velocity and return energy data for one or more detected objects.

In a possible implementation form of the method of the first aspect, thecontinued generation of the first type radar plots is performed byanalyzing range and radial velocity data obtained for hit range cells ofthe different image lines, and by

grouping neighboring hit range cells having matching range and radialvelocity data into a number of corresponding first type range radarplots.

In a possible implementation form of the method of the first aspect, thegeneration of the second type radar plots is initiated when scan datafor all image lines within said first full circular radar image has beenobtained.

In a possible implementation form of the method of the first aspect, thegeneration of the second type radar plots comprises:

analyzing range and azimuth data obtained for the hit range cells ofimage lines of a full circular radar image, and

grouping neighboring hit range cells having matching range and azimuthdata into a number of corresponding second type range radar plots,thereby obtaining second type radar plots for the full circular radarimage, each second type radar plot holding azimuth, range and returnenergy data for one or more detected objects.

In a possible implementation form of the method of the first aspect, thegeneration of full data type radar plots for said first full circularradar image is performed by

comparing range data of the obtained first and second type radar plotsof the full circular radar image, and

combining first and second type radar plots having matching range datainto corresponding full data type radar plots, each said full data typeradar plot thereby holding azimuth, range, velocity and return energydata for one or more detected objects.

In a possible implementation form of the method of the first aspect, themethod further comprises selecting irregular type radar plots based onfull data type radar plots having velocity data representing bothpositive and negative radial velocities.

In a possible implementation form of the method of the first aspect, afull data type radar plot is selected as an irregular type radar plotwhen the velocity data of the full data type radar plot representspositive and negative radial velocities with at least a predeterminedminimum velocity difference between the most positive radial velocityand the most negative radial velocity.

In a possible implementation form of the method of the first aspect, themethod further comprises selecting a full data type radar plot as aregular type radar plot when the velocity data of the full data typeradar plot represents positive radial velocities only.

In a possible implementation form of the method of the first aspect, afull data type radar plot is selected as a regular type radar plot whenthe velocity data of the full data type radar plot represents positiveand negative radial velocities with at maximum velocity differencebetween the most positive radial velocity and the most negative radialvelocity being less than said predetermined minimum velocity difference.

In a possible implementation form of the method of the first aspect, theFMCW radar system is configured to provide scan data indicative ofradial velocities within a predetermined positive velocity range and apredetermined negative velocity range of same size as the predeterminedpositive velocity range. In a possible implementation form of the methodof the first aspect, the predetermined minimum velocity differencebetween the most positive radial velocity and the most negative radialvelocity is at least 50%, such as at least 60%, such as at least 70%, orsuch as at least 75% of the combined predetermined positive and negativevelocity ranges. In a possible implementation form of the method of thefirst aspect, the FMCW radar system is configured to provide scan dataindicative of radial velocities within the range of −30 to +30 m/s. In apossible implementation form of the method of the first aspect, thepredetermined minimum velocity difference between the most positiveradial velocity and the most negative radial velocity is at least 45m/s.

In a possible implementation form of the method of the first aspect, themethod further comprises generating one or more unmanned aerial vehicle,UAV, tracks, where each UAV track is based on at least two irregulartype radar plots having a match between corresponding data of said atleast two irregular type radar plots. In a possible implementation formof the method of the first aspect, the match between corresponding dataof two irregular type radar plots comprises a match between radialvelocity data.

In a possible implementation form of the method of the first aspect, thematch between corresponding data of two irregular type radar plotscomprises a match between range data.

In a possible implementation form of the method of the first aspect, thematch between corresponding data of two irregular type radar plotscomprises a match between return energy data.

In a possible implementation form of the method of the first aspect, themethod further comprises selecting an irregular type radar plot as adiscarded irregular type radar plot, when the irregular type radar plotdoes not have a match with any irregular type radar plots.

In a possible implementation form of the method of the first aspect, themethod further comprises generating one or more bird tracks, where eachbird track is based on a match between corresponding data of at leasttwo, three or four regular type radar plots and/or second type radarplots having no match with a first type radar plot. In a possibleimplementation form of the method of the first aspect, the match betweencorresponding data of regular type radar plots and/or second type radarplots comprises a match between range data. In a possible implementationform of the method of the first aspect, the match between correspondingdata of regular type radar plots and/or second type radar plotscomprises a match between radial velocity data. In a possibleimplementation form of the method of the first aspect, the match betweencorresponding data of regular type radar plots and/or second type radarplots comprises a match between return energy data.

In a possible implementation form of the method of the first aspect, themethod further comprises determining if there is a match between data ofa discarded irregular type radar plot and corresponding data of agenerated bird track, and including the discarded plot into said birdtrack if there is a match, and if there is no match, then classifyingthe discarded plot as representing a “hovering vehicle” track.

In a possible implementation form of the method of the first aspect, themethod further comprises to determine for the plots of a generated UAVtrack: an outer energy sum being the sum of return energies for rangecells representing positive and negative radial velocity signals withinouter velocity ranges of the observed radial velocity range; and

a center energy sum being the sum of return energies for range cellsrepresenting radial velocity signals within a center range of theobserved radial velocity range, and/or a total energy sum being thetotal sum of return energies of range cells representing all radialvelocity signals of the observed radial velocity range.

In a possible implementation form of the method of the first aspect, themethod further comprises classifying the UAV track as a real UAV trackor non-real UAV track based at least partly on a comparison of thedetermined outer energy sum with the determined center energy sum and/orwith the determined total energy sum. In a possible implementation formof the method of the first aspect, the classification of the UAV trackas a real UAV track or non-real UAV track is further based at leastpartly on a comparison of the determined total energy sum with apredetermined maximum energy representing a predetermined maximum radarcross-section.

In a possible implementation form of the method of the first aspect, themethod further comprises:

updating a generated bird track with new regular type radar plots and/orsecond type radar plots having no match with a first type radar plot,

determining for said updated bird rack, a sum of return energies fromthe return energy data being hold by the radar plots representing saidbird track,

determining velocity, acceleration, direction and sinuosity of movementcurve from changing track data of said updated bird track, and

classifying the bird track as a small bird track, a medium bird track, alarge bird track, a flock of bird track, or as a non-bird track, basedon the determined sum of return energies, and based on the determinedvelocity, acceleration, direction and sinuosity of movement curve.

In a possible implementation form of the method of the first aspect, themethod further comprises forwarding in real time data for the classifiedtracks to a display unit, and displaying classified tracks based on thereceived track data on said display unit. In a possible implementationform of the method of the first aspect, the method further compriseforwarding data for the classified tracks to a storage unit, and storingthe classified track data by said storage unit.

It is an object of the invention to provide a system for generatingradar plots, which can be used for generating object tracks having ahigh probability for representing Unmanned Aerial Vehicles, UAVs. It isalso an object of the invention to provide a system for generatingobject tracks based on the obtained radar plots.

According to a second aspect there is provided a Frequency ModulatedContinuous Wave, FMCW, radar system comprising:

one or more antennas configured to transmit and receive FMCW radar wavesignals for scanning for objects, such as unmanned aerial vehicles,UAVs, within a full circular detection coverage range; and

processing circuitry configured to:

provide scan data based on transmitted and received FMCW radar signalsand azimuth position of the antenna(s); and

generate full data type radar plots based on obtained scan data, eachsaid full data type radar plot holding azimuth, range, radial velocityand received return energy data for one or more detected objects;wherein

the processing circuitry is further configured to:

select irregular type radar plots from full data type radar plots, saidirregular type radar plots having velocity data representing bothpositive and negative radial velocities within an observed radialvelocity range with at least a predetermined minimum velocity differencebetween the observed radial velocity with the largest positive radialvalue and the observed radial velocity with the largest absolutenegative value.

In a possible implementation form of the second aspect, the processingcircuitry is configured to generate one or more object tracks orunmanned aerial vehicle, UAV, tracks, where each object/UAV track isbased on at least two irregular type radar plots having a match betweencorresponding data of said at least two irregular type radar plots.

In a possible implementation form of the second aspect, the system isconfigured to provide scan data indicative of radial velocities within apredetermined positive velocity range and a predetermined negativevelocity range of same size as the predetermined positive velocityrange.

In a possible implementation form of the second aspect, thepredetermined minimum velocity difference between the observed radialvelocity with the largest positive value and the observed radialvelocity with the largest absolute negative value is at least 50%, suchas at least 60%, such as at least 70%, or such as at least 75% of thecombined predetermined positive and negative velocity ranges.

In a possible implementation form of the second aspect, the system isconfigured to provide scan data indicative of relative velocities withinthe range of −30 to +30 m/s.

In a possible implementation form of the second aspect, thepredetermined minimum velocity difference between the observed radialvelocity with the largest positive value and the observed radialvelocity with the largest absolute negative value is at least 45 m/s.

In a possible implementation form of the second aspect, the matchbetween corresponding data comprises a match between radial velocitydata.

In a possible implementation form of the second aspect, the matchbetween corresponding data comprises a match between range data.

In a possible implementation form of the second aspect, the matchbetween corresponding data comprises a match between return energy data.

In a possible implementation form of the second aspect, the processingcircuitry is configured to determine for the plots of a generatedobject/UAV track:

an outer energy sum being the sum of return energies for range cellsrepresenting positive and negative radial velocity signals within outervelocity ranges of the observed radial velocity range; and

a center energy sum being the sum of return energies for range cellsrepresenting radial velocity signals within a center range of theobserved radial velocity range, and/or

a total energy sum being the total sum of return energies of range cellsrepresenting all radial velocity signals of the observed radial velocityrange.

In a possible implementation form of the second aspect, the processingcircuitry is configured to classify the object/UAV track as a real UAVtrack or non-real UAV track based at least partly on a comparison of thedetermined outer energy sum with the determined center energy sum and/orwith the determined total energy sum.

In a possible implementation form of the second aspect, the processingcircuitry is configured to classify the object/UAV track as non-real UAVtrack when the determined outer energy sum is below a predeterminedfraction of the determined center energy sum, such as below 1/1000 ofthe center energy sum.

In a possible implementation form of the second aspect, the processingcircuitry is configured to classify the object/UAV track as non-real UAVtrack when the determined outer energy sum is below a predeterminedfraction of the determined total energy sum.

In a possible implementation form of the second aspect, the processingcircuitry is configured to classify the object/UAV track as a real UAVtrack or non-real UAV track based at least partly on a comparison of thedetermined total energy sum with a predetermined maximum energyrepresenting a predetermined maximum radar cross-section.

In a possible implementation form of the second aspect, the processingcircuitry is configured to classify the object/UAV track as a non-UAV orlarge UAV track when the determined total energy sum is above apredetermined maximum energy representing a predetermined maximum radarcross-section, such as a maximum radar cross-section of 1 m².

In a possible implementation form of the second aspect, the processingcircuitry is configured to classify the object/UAV track as a real UAVtrack when the determined outer energy sum is above a predeterminedfraction of the determined center energy sum and/or above apredetermined fraction of the determined total energy sum, and when thedetermined total energy sum is below a predetermined maximum energyrepresenting a predetermined maximum radar cross-section.

In a possible implementation form of the second aspect, the processingcircuitry is configured to forward in real time data representing theclassified tracks to a display unit, said display unit being configuredfor displaying classified tracks based on the received track data.

In a possible implementation form of the second aspect, the processingcircuitry is configured to forward data representing the classifiedtracks to a storage unit, said storage unit being configured for storingthe classified track data.

In a possible implementation form of the second aspect, the processingcircuitry is configured to:

provide scan data representing range cells within image lines ofcircular radar images, where each radar image holds a number of imagelines defining a full circular radar image, with each image linecorresponding to an azimuth orientation, and where each image line holdsa number of range cells, with each range cell corresponding to adistance to the radar antenna(s), and wherein an object, which isdetected within an azimuth orientation and range to the radarantenna(s), is represented by a number of hit range cells in one or moreimage lines, and wherein each hit range cell holds data for energy ofreturned signal(s) and data for radial velocity or velocities based onDoppler frequency signals, said scan data thereby for each hit rangecell holding information of range, azimuth orientation, energy ofreturned radar wave signals, and radial velocity or velocities of adetected object.

In a possible implementation form of the second aspect, the processingcircuitry is configured to generate full data type radar plots based ongrouping of neighboring hit range cells within one or more image linesof a full circular radar image having matching range, azimuth and radialvelocity data.

It should be understood that the processing system of the radar systemof the second aspect may be configured for generating full data typeradar plots according to one or more possible implementation forms ofthe first aspect. It should also be understood that the processingsystem of the radar system of the second aspect may be configured forgenerating object tracks and/or for classifying object tracks accordingto one or more possible implementation forms of the first aspect.

It is an object of the invention to provide a system, which can identifyobject tracks representing real Unmanned Aerial Vehicles, UAVs.

According to a third aspect there is provided a Frequency ModulatedContinuous Wave, FMCW, radar system comprising:

one or more antennas configured to transmit and receive FMCW radar wavesignals for scanning for objects, such as unmanned aerial vehicles,UAVs, within a full circular detection coverage range; and

processing circuitry configured to:

provide scan data based on transmitted and received FMCW radar signalsand azimuth position of the antenna(s), said scan data representingrange cells within image lines of circular radar images, where eachradar image holds a number of image lines defining a full circular radarimage, with each image line corresponding to an azimuth orientation, andwhere each image line holds a number of range cells, with each rangecell corresponding to a distance to the radar antenna(s), and wherein anobject, which is detected within an azimuth orientation and range to theradar antenna(s), is represented by a number of hit range cells in oneor more image lines, and wherein each hit range cell holds data forenergy of returned signal(s) and data for radial velocity or velocitiesbased on Doppler frequency signals, said scan data thereby for each hitrange cell holding information of range, azimuth orientation, energy ofreturned radar wave signals, and radial velocity or velocities of adetected object; whereinthe processing circuitry is further configured to:generate full data type radar plots based on obtained range cell scandata, each said full data type radar plot holding azimuth, range, radialvelocity and received return energy data for one or more detectedobjects;select irregular type radar plots from full data type radar plots, saidirregular type radar plots having velocity data representing bothpositive and negative radial velocities within an observed radialvelocity range;generate one or more object tracks or unmanned aerial vehicle, UAV,tracks, where each object/UAV track is based on at least two irregulartype radar plots having a match between corresponding data of said atleast two irregular type radar plots;determine for the plots of a generated object/UAV track:an outer energy sum being the sum of return energies for range cellsrepresenting positive and negative radial velocity signals within afirst and a second outer velocity range outside a center range of theobserved radial velocity range;a center energy sum being the sum of return energies for range cellsrepresenting radial velocity signals within the center range of theobserved radial velocity range, and/or a total energy sum being thetotal sum of return energies of range cells representing all radialvelocity signals of the observed radial velocity range; andwherein the processing circuitry is further configured to:classify the object/UAV track as a real UAV track or non-real UAV trackbased at least partly on a comparison of the determined outer energy sumwith the determined center energy sum and/or with the determined totalenergy sum.

In a possible implementation form of the third aspect, the processingcircuitry is configured to classify the object/UAV track as a real UAVtrack or non-real UAV track based at least partly on a comparison of thedetermined total energy sum with a predetermined maximum energyrepresenting a predetermined maximum radar cross-section.

In a possible implementation form of the third aspect, the processingcircuitry is configured to classify the object/UAV track as a real UAVtrack when the determined outer energy sum is above a predeterminedfraction of the determined center energy sum and/or above apredetermined fraction of the determined total energy sum, and when thedetermined total energy sum is below a predetermined maximum energyrepresenting a predetermined maximum radar cross-section.

In a possible implementation form of the third aspect, the processingcircuitry is configured to classify the object/UAV track as non-real UAVtrack when the determined outer energy sum is below a predeterminedfraction of the determined center energy sum, such as below 1/1000 ofthe center energy sum.

In a possible implementation form of the third aspect, the processingcircuitry is configured to classify the object/UAV track as non-real UAVtrack when the determined outer energy sum is below a predeterminedfraction of the determined total energy sum.

In a possible implementation form of the third aspect, the processingcircuitry is configured to classify the object/UAV track as a non-UAV orlarge UAV track when the determined total energy sum is above apredetermined maximum energy representing a predetermined maximum radarcross-section, such as a maximum radar cross-section of 1 m².

In a possible implementation form of the third aspect, the processingcircuitry is configured to determine radial velocity boundaries for thecenter velocity range, and determine radial velocity boundaries for thefirst outer velocity range including negative radial velocity signalsand radial velocity boundaries for the second outer velocity rangeincluding positive radial velocity signals, wherein the determination ofthe velocity boundaries of the first and second velocity ranges is basedon the radial velocity boundaries for the center velocity range and thetotal observed velocity range.

In a possible implementation form of the third aspect, the processingcircuitry is configured to determine radial velocity boundaries for thecenter velocity range based on variations in observed energy levels ofreturned radar signals as a function of radial velocity.

In a possible implementation form of the third aspect, the processingcircuitry is configured to determine a decrease in observed energy levelto a local minimum on both sides of the center velocity of the observedvelocity range, and determine the radial velocity boundaries for thecenter velocity range as the radial velocities for which the observedenergy level on both sides of the center velocity has increased by apredetermined factor from the observed local minima. It is preferredthat the predetermined incremental factor is about 2 or 3 dB.

In a possible implementation form of the third aspect, the processingcircuitry is configured to generate full data type radar plots based ongrouping of neighboring hit range cells within one or more image linesof a full circular radar image having matching range, azimuth and radialvelocity data.

In a possible implementation form of the third aspect, the processingcircuitry is configured to forward in real time data representing theclassified tracks to a display unit, wherein the display unit isconfigured for displaying classified tracks based on the received trackdata.

In a possible implementation form of the third aspect, the processingcircuitry is configured to forward data representing the classifiedtracks to a storage unit, said storage unit being configured for storingthe classified track data.

It should be understood that the processing system of the radar systemof the third aspect may be configured for generating full data typeradar plots according to one or more possible implementation forms ofthe first aspect. It should also be understood that the processingsystem of the radar system of the third aspect may be configured forgenerating object tracks and/or for classifying object tracks accordingto one or more possible implementation forms of the first aspect.

It is an object of the invention to provide a system which can bothtrack UAVs and make a distinction between the tracked UAVs.

According to a fourth aspect there is provided an unmanned aerialvehicle, UAV, system comprising:

a control station for controlling a first co-operating unmanned aerialvehicle, UAV, the control station being configured for exchangingtelemetric data with said first UAV, including data for commanding saidfirst UAV to follow a flight path based on flight plan commands receivedfrom the control station, and said first UAV possibly being providedwith a transponder holding identification information, ID, for saidfirst UAV, and said first UAV and the control station possibly beingconfigured for exchanging transponder data;a radar system or ground based radar system configured to scan forobjects within a detection coverage range and to provide scan dataindicative of objects detected within the coverage range; andprocessing circuitry configured to:generate radar plots for one or more detected objects based on scan datareceived from the radar system;generate and store one or more UAV object tracks based on matching radarplots, each UAV object track holding object data corresponding to dataof matching plots;receive telemetric data and/or transponder data for said first UAV;determine for each UAV object track whether there is a match betweendata of the UAV object track and corresponding telemetric data and/ortransponder data for said first UAV; andclassify the UAV of a UAV object track as a first co-operating UAV whenpredetermined matching conditions are fulfilled for corresponding dataof the UAV object track and received telemetric data and/or transponderdata, and classify the UAV of a UAV object track as a secondnon-co-operating UAV when the predetermined matching conditions are notfulfilled.

By comparing telemetric and/transponder data with track data based onradar scan data, it is possible to divide the obtained tracks into knownUAV tracks, representing a UAV which can be controlled, and into unknownUAV tracks, representing a UAV which cannot be controlled.

In a possible implementation form of the fourth aspect, the radar systemcomprises a Doppler type radar, such as a Frequency Modulated ContinuousWave, FMCW, radar.

In a possible implementation form of the fourth aspect, the processingcircuitry is configured for generating UAV object tracks holding datarepresenting position, radial velocity and size for a tracked objectbased on data of matching radar plots obtained from the received scaninformation. The position data may include range and azimuth relative tothe radar system, the velocity data may be radial velocity/Dopplervelocity, and the size data may be determined based on energy of returnscan signals within plots forming the object track.

In a possible implementation form of the fourth aspect, the firstco-operating UAV holds a global positioning system, GPS, and thetelemetric data forwarded by the control station to the processingcircuitry for said first co-operating UAV holds position data, which arebased on GPS data. Such position data may include distance, azimuth,elevation, velocity, and/or direction of travel relative to the controlstation.

In a possible implementation form of the fourth aspect, the firstco-operating UAV holds a transponder with ID data, and the transponderdata forwarded by the first UAV to the control station represents IDdata, and possibly also position data, such as altitude or elevationdata.

In a possible implementation form of the fourth aspect, thepredetermined matching conditions to be fulfilled between data of thestored tracks and received telemetric data and/or transponder datacomprise a match between position data.

In a possible implementation form of the fourth aspect, thepredetermined matching conditions to be fulfilled between data of thestores tracks and received telemetric data and/or transponder datacomprise a match between velocity data and/or a match between size data.

In a possible implementation form of the fourth aspect, the processingcircuitry is configured to determine when a match condition is fulfilledfor a set of corresponding data based on a predetermined thresholddifference between the data being matched.

In a possible implementation form of the fourth aspect, then when theUAV of a UAV object track is classified as a second non-co-operatingUAV, the control station is configured to:

generate and forward flight plan commands to the first co-operating UAVbased at least partly on object data from the object track of the secondnon-co-operating UAV.

In a possible implementation form of the fourth aspect, then when theUAV of a UAV object track is classified as a second non-co-operatingUAV, the control circuitry is configured to:

generate and forward action commands to the first UAV based oninformation obtained from the object track of the second UAV, andwherein

the first co-operating UAV is configured to perform an action based atleast partly on the received action commands.

In a possible implementation form of the fourth aspect, the controlstation is configured to generate and forward flight disturbing actioncommands to the first co-operating UAV based on information obtainedfrom the object track of the second non co-operating UAV.

In a possible implementation form of the fourth aspect, the firstco-operating UAV is configured to execute a flight-route or flight plandisturbing action for the second non co-operating UAV based on thereceived flight disturbing action commands.

In a possible implementation form of the fourth aspect, the flight-routeor flight plan disturbing action to be executed may be to divert thefirst co-operating UAV towards the second non co-operating UAV to inducea collision between the first and second UAVs.

In a possible implementation form of the fourth aspect, the controlstation is configured to generate the flight plan commands and/or actioncommands based on position data obtained from the object track of thesecond non-co-operating UAV. Here, position data may include range andazimuth relative to the radar system.

In a possible implementation form of the fourth aspect, the controlstation is configured to generate the flight plan commands and/or actioncommands based on size data obtained from the object track of the secondnon-co-operating UAV. Here, size data may be determined based on energyof return scan signals within plots forming the object track of thesecond non-co-operating UAV.

In a possible implementation form of the fourth aspect, the controlstation is configured to generate the flight plan commands and/or actioncommands to the first co-operating UAV based at least partly on receivedtelemetric data and/or transponder data for the first co-operating UAV.

In a possible implementation form of the fourth aspect, the firstco-operating UAV holds a camera, and the first UAV is configured fortransmitting telemetric data including a video signal to the controlstation, and the control station is configured for generating the flightpath information based as least partly on the received video signal.

In a possible implementation form of the fourth aspect, the controlstation is configured to generate and forward the flight planinformation based on position data obtained from the object track of thesecond non co-operating UAV until the second non co-operating UAV isdetected within the received video signal.

In a possible implementation form of the fourth aspect, then when secondnon co-operating UAV is detected within the received video signal, thecontrol station is configured to generate and forward the flight planinformation based on the received video signal.

In a possible implementation form of the fourth aspect, the processingcircuitry is configured to:

generate full data type radar plots based on obtained scan data, eachsaid full data type radar plot holding azimuth, range, radial velocityand received return energy data for one or more detected objects;

select irregular type radar plots from full data type radar plots, saidirregular type radar plots having velocity data representing positiveand negative radial velocities within an observed radial velocity range;

generate one or more UAV object tracks, where each UAV object track isbased on at least two irregular type radar plots having a match betweencorresponding data of said at least two irregular type radar plots.

In a possible implementation form of the fourth aspect, the selectedirregular type radar plots have velocity data representing positive andnegative radial velocities with at least a predetermined minimumvelocity difference between the observed radial velocity with thelargest positive value and the observed radial velocity with the largestabsolute negative value.

In a possible implementation form of the fourth aspect, a generated UAVtrack is based at least partly on radar plots having matching radialvelocity data.

In a possible implementation form of the fourth aspect, a generated UAVtrack is based at least partly on radar plots having matching rangedata.

In a possible implementation form of the fourth aspect, a generated UAVtrack is based at least partly on radar plots having matching returnenergy data.

In a possible implementation form of the fourth aspect, the processingcircuitry is configured to match return energy data of two irregulartype radar plots by:

determining a total sum of return energies representing all radialvelocity signals for each of the two irregular type radar plots beingmatched, and

determining if there is a match between the obtained total sum of returnenergies.

In a possible implementation form of the fourth aspect, the processingcircuitry is configured to match return energy data of two irregulartype radar plots by:

determining a sum of center return energies corresponding to a centeredradial velocity span within the observed radial velocity range for eachof the two irregular type radar plots being matched, and

determining if there is a match between the obtained sum of centerreturn energies.

It should be understood that the processing system of the radar systemof the fourth aspect may be configured for generating full data typeradar plots according to one or more possible implementation forms ofthe first aspect. It should also be understood that the processingsystem of the radar system of the fourth aspect may be configured forgenerating object tracks and/or for classifying object tracks accordingto one or more possible implementation forms of the first aspect.

It should be understood that the radar system of the first aspect mayinclude the possible implementation forms of the radar systems of thesecond, third and/or fourth aspects, which implementation forms have notalready been included in the first aspect. Also, the radar systems ofthe second aspect may include the possible implementation forms of theradar systems of the first, third and/or fourth aspects, whichimplementation forms have not already been included in the secondaspect. Also, the radar systems of the third aspect may include thepossible implementations forms of the radar systems of the first, secondand/or fourth aspects, which implementation forms have not already beenincluded in the third aspect. Similarly, the radar systems of the fourthaspect may include the possible implementations forms of the radarsystems of the first, second and/or third aspects, which implementationforms have not already been included in the fourth aspect.

The foregoing and other objects are achieved by the features of theindependent claims. Further implementation forms are apparent from thedependent claims, the description and the figures. These and otheraspects of the invention will be apparent from the embodiments describedbelow.

BRIEF DESCRIPTION OF THE DRAWINGS

In the following detailed portion of the present disclosure, theinvention will be explained in more detail with reference to the exampleembodiments shown in the drawings, in which:

FIG. 1a is a schematic block diagram illustrating the basic structure ofa scanning radar system according to an example embodiment;

FIG. 1b is a block diagram illustrating functional components of aFrequency Modulated Continuous Waves, FMCW, transceiver being part ofthe radar system of FIG. 1a according to an example embodiment.

FIG. 2 illustrates a radar image with image lines and range cellsaccording to an example embodiment;

FIG. 3 illustrates transmission of radar waves in the form of FrequencyModulated Continuous Waves, FMCW, waves according to an exampleembodiment;

FIGS. 4a and 4b illustrates a range-Doppler map with micro-Dopplersignatures according to an example embodiment;

FIG. 5 is a flow diagram illustrating generation of data to be used forplot generation according to an example embodiment;

FIG. 6 is a flow diagram illustrating generation of first type radarplots holding range, radial velocity and return energy informationaccording to an example embodiment;

FIG. 7 is a flow diagram illustrating generation of second type radarplots holding range, azimuth and return energy information according toan example embodiment;

FIG. 8 is an overview flow diagram illustrating processing stepsperformed for reaching a classification of a detected object accordingto an example embodiment;

FIG. 9 is a flow diagram illustrating generation of full type radarplots holding range, azimuth radial velocity and return energyinformation according to an example embodiment;

FIG. 10 is a flow diagram illustrating division of obtained full typeradar plots into regular and irregular plots based on velocityinformation according to an example embodiment;

FIG. 11 is an overview flow diagram illustrating generation of UnmannedAerial Vehicle, UAV, tracks according to an example embodiment;

FIG. 12 is an overview flow diagram illustrating generation of birdtracks according to an example embodiment;

FIG. 13 is a detailed flow diagram illustrating generation of birdtracks according to an example embodiment;

FIG. 14 is a detailed flow diagram illustrating generation of UnmannedAerial Vehicle, UAV, tracks according to an example embodiment;

FIG. 15 is a flow diagram illustrating classification of obtained tracksaccording to an example embodiment;

FIG. 16 is a graph illustrating reflected energy as a function of radialvelocity for a tracked Unmanned Aerial Vehicle, UAV, according to anexample embodiment;

FIG. 17 is a schematic block diagram illustrating the basic structure ofan Unmanned Aerial Vehicle, UAV, system according to an exampleembodiment;

FIG. 18 is an overview flow diagram illustrating processing stepsincluding plot generation, track generation and classification of adetected object based on data obtained by the system of FIG. 17according to an example embodiment;

FIG. 19 is an overview flow diagram illustrating generation of UnmannedAerial Vehicle, UAV, tracks based on data obtained by the system of FIG.17 according to an example embodiment; and

FIG. 20 is a block diagram illustrating exchange of signals betweenparts of the system of FIG. 17 according to an example embodiment.

DETAILED DESCRIPTION

FIG. 1a is a schematic block diagram illustrating the basic structure ofa scanning radar system according to an example embodiment. The systemcomprises a Frequency Modulated Continuous Wave, FMCW, radar system 101electronically connected to a computer system 102. Generated output datamay be communicated to an external command and control system 103, wherethe data may be communicated by live data streaming, where for exampleExtensible Markup Language, XML, may be used for streaming.

The FMCW radar system 101 holds a transmitting horn antenna 110 and areceiving horn antenna 111 with a splitting plane 113 arranged betweenthe two antennas 110 and 111 in order to prevent false reflections. Theantennas 110, 111 are enclosed by a radome 114 made of a plastic type,which gives no or very low reflections of the radar waves, to therebyavoid disturbance of the Doppler frequency shift. The splitting plane113 is arranged very close to the radome 114, again to prevent falsereflections. The antennas 110, 111 are mounted to an upright support 112a, which is rotatably mounted to a horizontal support 112 b, where thehorizontal support is configured for rotating 115 the upright 112 a withthe antennas 110, 111 at a rotational speed of 45 rounds per minute,rpm. An azimuth encoder is provided at the horizontal support 112 b,which encoder is configured for encoding and communicating the degree ofrotation, and thereby the azimuth angle, of the antennas 110, 111, at avery high precision. The antenna system 101 is configured fortransmitting FMCW radar signals in the range of 8.7 to 10 GHz at atransmission power about 4 Watt. The horn antennas 110 and 111 covers analmost square beam window having a beam height about 10° and a beamwidth of about 10°. Such a configuration of the antenna system 101results in a detection coverage range of about 1 km. The beam width of10° is much wider than normal for FMCW radar systems, where a beam widtharound 1° is usual. By using a wide beam width of 10° the target orobject being detected will be exposed to the transmitted radar signalsfor a longer time, resulting in more time for data processing in orderto determine the Doppler frequency shift. The targets or objects beingexposed to the radar signals may include one or more Unmanned AerialVehicles, UAVs, 105 and one or more birds 106.

The FMCW radar system 101 holds electronic front end circuitry 116,which is also mounted to the upright 112 a, for feeding the transmittingantenna 110 and for receiving radar return signals being received by thereceiving antenna 111. The front end circuitry 116 is enclosed by analuminium shield 117, which shields for electronic noise signals toenter the circuitry 116, and which also acts a heat sink. The front endcircuitry 116 is electronically connected to back end circuitry beingpart of the azimuth encoder for communicating the azimuth angle. Thefront end circuitry 116 and the back end circuitry are electronicallyconnected to the computer system 102, whereby electronic circuitry ofthe computer system 102, the front end circuitry 116 and the back endcircuitry together provide processing circuitry for processing signalsforwarded to and received from the antenna system 101 and for generatingradar plots. The processing circuitry may also perform the processingfor generating object tracks based on the plots and for classifying theobjects of the tracks.

The electronic signals are transferred via a glass fibre cable from thefront end circuitry 116 to a rotary joint at the horizontal support 112b, which is connected to the computer system 102 by cables.

The functional components of the front end circuitry 116 and the backend circuitry is illustrated in FIG. 1b , which is a block diagramshowing electronic and radar components of a Frequency ModulatedContinuous Waves, FMCW, transceiver according to an example embodiment.The transmission of radar wave signals is controlled by a digitalcontrol words received by a FMCW sweep generator 116 a, which holds avoltage controlled oscillator, VCO, and generates a single-sloped shapedFMCW transmission sweep signal, which is fed to a −3 dB coupler 116 b.The coupler 116 b branches off part of the signal to a mixing stage 116f, with the main part of the sweep signal being forwarded to a digitalattenuator 116 c for azimuth attenuation, with the output of the azimuthattenuator 116 c being sent to a power amplifier 116 d. The amplifiedsweep radio frequency, RF, signal is finally radiated as electromagneticradar wave signals by the transmitting antenna 110. The returned radarwave signals are received by the receiving antenna 111, which convertsthe received electromagnetic waves back into a RF signal. The receivedRF signal is amplified by a low noise amplifier 116 e, with theamplified received signal being fed into the mixing stage 116 f. Theoutput of the mixing stage 116 f is the difference between thetransmitted signal and the received signal. The difference signal fromthe mixing stage 116 f is filtered by a low pass frequency filter 116 gin order to block unwanted mixing frequencies, and then amplified atamplifier 116 h before being converted from analog to digital signals atanalog to digital converter 116 i. The digital signal being output fromthe converter 116 i is the signal output from the front end circuitry116, and holds information from which range, radial velocity and returnenergy of detected objects or targets can be determined.

The azimuth information from the encoder together with attenuatorsettings from the attenuator 116 c are then added to the output from theconverter 116 i by the “Add azimuth info” back end circuitry 116 j,whereby digital scan data holding information from which azimuth angle,range, radial velocity and return energy of detected objects or targetscan be determined. In an optional embodiment, the FMCW radar system 101is also configured for scanning in the elevation, and for thisembodiment, elevation angle information may also be added to the outputfrom the converter 116 i at the back end circuitry 116 j.

The digital signal being output from the converter 116 i and therebyalso the digital scan data output from the back end circuitry 116, holdsthe information of the output difference signal from the mixing stage116 f, which difference signal holds information of the amplitude of thereceived return signal, the time delay, Δt, between the transmitted andreceived signal and the beat frequency or frequency difference, Δf,between the rising edges of the transmitted and received signals. Thebeat frequency also includes the Doppler frequency shift, f_(D), andusing the results of several consecutive sweep signals, the range andDoppler frequency shift or Doppler velocity can be determined by use ofa double Fourier transform on the digital converted sweeps signals, andthe result can be presented in a range-Doppler map.

The scanning operating and presentation of data in range-Doppler maps isfurther illustrated in FIGS. 2, 3 and 4.

The FMCW radar system 101 scans for objects within a full circular rangeof 360°, and scan data is obtained with reference to a radar image asillustrated in FIG. 2. FIG. 2 shows and example embodiment of a radarimage 200, which is divided in 80 image lines, 201, to cover a fullazimuth range, 204, of 360° for an image. The radar 101 rotates with 45rounds per minute, rpm, where a full radar image 200 is obtained foreach rotation. Each image line is divided in 1356 range cells, 203, andcovers an azimuth range of 4.5°, 202. The radar, 101, transmits 100 FMCWsweep signals, 205, per image line, which are mixed with correspondingreturned radar wave signals, and from a mixed set of radar signals,where each set represents a full 100 FMCW sweep signals, a Doppler maprepresenting the corresponding image line, 201, having a certain azimuthrange, is generated.

The antennas 110, 111 of the radar system 101 has a beam width of about10°, which is about the double of the azimuth range for an image line201. This allows the transmission and receipt of the 100 FMCW sweepsignals within the time frame of which an image line 201 is covered bythe antennas 110, 111 during the rotation of the radar system 101.

The FMCW sweep signals may have a single-sloped shape, as illustrated inFIG. 3, which shows a couple of FMCW radar waves 300 in a time-frequencydiagram, 301, 302, according to an example embodiment.

FIG. 4a illustrates a range-Doppler map 400 with micro-Dopplersignatures according to an example embodiment, where range is along thex-axis, 401, and radial velocity/Doppler velocity is along the y-axis,402, with maximum radial velocities of +30 m/s and −30 m/s. Therange-Doppler map 400 of FIG. 4a shows an example of the spread inradial velocities for 6 range cells. For range cell 4 there is a spreadin the observed radial velocity indicated by A, 403, where the full dot,404, indicates the radial velocity, for which the received return signalhas the highest amplitude or return energy, while the smaller dots oneach side of the full dot, 404, represents radial velocities withsmaller amplitude or return energy in the received return signal. Forrange cell 4, the main contribution in radial velocity indicated by thedot 404 may come from the torso of a target, such as a bird orhelicopter, and represent the radial/Doppler velocity of the target,while the observed velocity-sidebands around the dot, 404, are referredto as micro-Doppler signatures and may represent flapping motion of birdwings or propeller blades of a helicopter.

The range-Doppler map may be calculated as a range-Doppler matrix, wherea column of the matrix represents the velocity detection span for agiven individual target range or range cell, and a row represents therange detection span for a given individual target velocity range. Thevelocity column may be referred to as a so-called Doppler signature, andthe range-Doppler map/matrix then consists of the Doppler signatures ofall the individual target ranges or range cells. Each cell, which isreferred to as a bin, within the range-Doppler matrix then represents acertain range cell, and a certain radial velocity range. This isillustrated in FIG. 4b , which shows two Doppler signatures, 405 a and405 b, for two different target ranges or range cells. The amount ofreceived return energy is indicated by one or more “x” for each bin ofthe Doppler signatures, 405 a and 405 b. Both Doppler signatures, 405 aand 405 b, have velocity sidebands or micro-Doppler signatures on bothsides of a main Doppler velocity, where the bins with “xx” may representthe torso of a target, while the bins with one “x” may representflapping or rotating motions of a target.

The Doppler signature 405 a holds three neighboring bins with observedradial velocities given a radial velocity spread A, 406 a. It is notedthat all the observed velocities within the spread 406 a are positive,indicating that all target parts giving a return signal are moving awayfrom the radar system 101 at the time of observation. The Dopplersignature 405 b holds four bins with observed radial velocities given aradial velocity spread A, 406 b. It is noted that the observedvelocities within the spread 406 b are both positive and negative, withthe highest return energy being observed for a bin with negative radialvelocity, indicating that the torso of the target is moving in thedirection of the radar system 101, while other parts of the target aremoving in both radial directions of the radar system 101 at the time ofobservation. The Doppler signatures 405 a, 405 b of FIG. 4b each holds 8bins, but for the radar system 101, which is configured for 100 FMCWsweep signals, 205, per image line, 201, then the obtained Dopplersignatures has 100 bins, with 50 bins for positive radial velocities and50 bins for negative radial velocities. With 1356 range cells, 203,within each image line, 201, then for each image line, 201, arange-Doppler map/matrix holding 100 rows and 1356 columns is generatedfor each image line, 201. For 80 image lines, 201, then 80 range-Dopplermaps/matrices have to be generated to cover a full radar image, 200,where each range-Doppler map/matrix corresponds to an image line withina defined 4.5° azimuth range. It is noted that each bin, for which thereis a hit-target, holds information of the amplitude or return energy ofthe received radar signal, and the position of the bin within therange-Doppler map/matrix gives the radial velocity of the target and thedistance to the target, while the azimuth angle is given by the positionof the image line, 201, within the radar image, 200.

An important feature of the present disclosure is to divide the processof generating data for the full data type radar plots into severalsteps, to thereby optimize the use of processing power. This isillustrated in the FIGS. 5, 6 and 7.

FIG. 5 is a flow diagram illustrating generation of data to be used forplot generation according to an example embodiment. The whole process ofFIG. 5 is named “plot input data generation”, 500, and starts by thedigital scan data, 501, being output from front and back end circuitry116 of FIG. 1b . The digital scan data then goes through a clutterfiltering process, 502, to separate target data from clutter data, whichmay be a digital filtering process based on Doppler content andamplitude content of the obtained data. Different processes of clutterfiltering are known in the art of radar scanning.

The received and filtered data are then stored, where the first set ofdata to be stored is the scan data for the first image line beingscanned, which data represents difference signals between transmit andreturn signals for each range cell in the first image line, energy forthe return signals, and azimuth angle for the first image line position.A double Fourier transform is used on the stored data to therebygenerate and store a range-Doppler velocity data set or map with returnenergies for the first image line, step 503. The obtained range-Dopplervelocity data set or map for the first image line can now be used forinitiating the generation of range-Doppler velocity plots, 504, see FIG.6

The procedure of step 503 is repeated in step 505 for the next imageline, where scan data for the next image line being scanned is stored,which data represents difference signals between transmit and returnsignals for each range cell in the next image line, energy for thereturn signals, and azimuth angle for the next image line position. Adouble Fourier transform is used on the stored data to thereby generateand store a range-Doppler velocity data set or map with return energiesfor the next image line, and the obtained range-Doppler data set or mapfor the next image line can now be used for further generation of therange-Doppler velocity plots, 506.

The procedure of step 505 is repeated for each image line during a full360 degree scan rotation to obtain data for the full circular radarimage, step 507. Each range cell of the full radar image having a hitnow holds data for: energy of returned signal(s), range from position ofrange cell, azimuth from image line position, and radial velocity orvelocities from Doppler shift(s) and mapped in the range-Doppler maps.Range, azimuth, and return energy data for all image lines of the fullradar image is now used for generation of range-azimuth plots, 508, seeFIG. 7.

FIG. 6 is a flow diagram illustrating generation of first type radarplots or range-Doppler velocity plots holding range, radial velocity andreturn energy information according to an example embodiment. The wholeprocess of FIG. 6 is named “range-Doppler velocity plot generation”,600, and starts by the generated range-Doppler velocity data setincluding return energy data for the first image line being output atstep 504 from the “plot input data generation”, 500.

The generation of the first type radar plots or range-Doppler velocityplots is initiated at step 601, in which velocity and range data for thefirst generated range-Doppler velocity data set for the first image lineis analysed. Based on this analysis, neighboring range cells havingmatching velocity and range data (if any) are grouped into one or morecorresponding range-Doppler velocity plots. Examples of matchingconditions are known in the art of radar scanning and plot generation,but a match condition may be fulfilled for a set of corresponding data,when the difference between the data being matched is below apredetermined threshold difference. Thus, there may be a maximumthreshold difference in range for defining neighboring range cells beingmatched, and there may be a maximum threshold difference in radialvelocities of these neighboring range cells before the cells are matchedin a plot. The generated range-Doppler velocity plots including returnenergy data are stored, steps 602 and 607.

The generation of the first type radar plots or range-Doppler velocityplots proceeds at step 604, and is based on the generated range-Dopplervelocity data set including return energy data for the next image linebeing output at step 506 from the “plot input data generation”, 500,while also being based on the previously generated range-Dopplervelocity data set including return energy data for the first image linebeing, step 603. The procedure in step 604 is similar to the procedureof step 601, and velocity and range data for the generated range-Dopplervelocity data sets for the first and next image lines are analysed, andneighboring range cells having matching velocity and range data aregrouped into one or more corresponding range-Doppler velocity plots. Thegenerated range-Doppler velocity plots including return energy data arestored, steps 605 and 607. In order to form a plot, there need to be atleast two neighboring range cells having matching data, but it ispreferred that in order to form at plot, there needs to be at leastfour, five or six neighboring range cells having matching data.

The procedure of step 604 is repeated, step 606, for data sets obtainedfor the following image lines, until data sets for each image line of afull circular radar image have been analysed. Thus, velocity and rangedata for the generated range-Doppler velocity data sets for a new imageline are analysed together with the already received data sets for theprevious image lines, and neighboring range cells having matchingvelocity and range data are grouped into one or more correspondingrange-Doppler velocity plots. The generated range-Doppler velocity plotsincluding return energy data are stored, steps 605 and 607. Therange-Doppler velocity plots stored at step 607 may be used as inputswhen combining plots into full data type plots, step 608. See FIG. 9 forcombination of plots.

FIG. 7 is a flow diagram illustrating generation of second type radarplots or range-azimuth plots holding range, azimuth and return energyinformation according to an example embodiment. the whole process ofFIG. 7 is named “range-azimuth plot generation”, 700, and starts at step701 by the generated range, azimuth and return energy data set for thefull circular radar image being output at step 508 from the “plot inputdata generation”, 500.

The generation of the second type radar plots or range-azimuth plots fora full radar image is performed at step 702, in which range and azimuthdata for range cells of each image line within the full circular radarimage are analysed. Based on this analysis, neighboring range cellshaving matching azimuth and range data are grouped into one or morecorresponding range-azimuth plots. Also here, a match condition may befulfilled for a set of corresponding data, when the difference betweenthe data being matched is below a predetermined threshold difference.Thus, there may be a maximum threshold difference in range for definingneighboring range cells being matched, and there may be a maximumthreshold difference in azimuth range of these neighboring range cellsbefore the cells are matched in a plot. The generated range-azimuthplots including return energy data for the full circular radar image arestored, step 703. The range-azimuth plots stored at step 703 may be usedas inputs when combining plots into full data type plots, step 704. SeeFIG. 9 for combination of plots. Also here, there need to be at leasttwo neighboring range cells having matching data, while it is preferredthat in order to form at plot, there needs to be at least four, five orsix neighboring range cells having matching data.

FIG. 8 is an overview flow diagram illustrating processing stepsperformed for reaching a classification for a detected object accordingto an example embodiment. The process map of FIG. 8 starts with plotinput data being generated at process 500. Based on the plot input data,range-Doppler velocity plots are generated, process 600, and stored,step 607 of process 600. Also range-azimuth plots are generated, process700, and stored, step 703 of process 700.

For a full circular radar scan, the range-Doppler velocity plots ofprocess 700 are generated during the scan, starting when scan data areobtained for the first image line, while the range-azimuth plots arefirst generated when a full scan has been performed. When the first setof range-azimuth plots have been generated for the first circular radarscan, and thereby for the first full radar image, the process proceedsby comparing and combining the obtained range-Doppler velocity plots,608, and range-azimuth plots, 704, into full data type plots, step 801,which is further described in connection with FIG. 9. It is noted thatduring the following circular radar scan, new range-Doppler plots aregenerated and stored during the scan, while new range-azimuth plots arefirst generated and stored when the following circular radar scan iscompleted. This procedure of plot generation is repeated for each fullcircular radar scan.

When comparing the obtained range-Doppler velocity plots andrange-azimuth plots at step 801, the range-azimuth plots, which cannotbe matched with a range-Doppler velocity plot, is forwarded to a socalled “Bird tracker” 806 via step 804. The range-Doppler velocityplots, which cannot be matched with a range-azimuth plot is discarded.

In step 801, the remaining plots are combined into full data type plots,which now hold range, azimuth, radial velocity, and return energy datafor detected objects forming part of a plot. The next step is to dividethe full data type plots based on Doppler velocity profile, step 802,which is further described in connection with FIG. 10. The combinedplots are divided into plots with irregular Doppler velocity profile,step 803, and plots with regular Doppler velocity profile, step 804. Theplots with irregular Doppler velocity profile are fed to a so called“Unmanned Aerial Vehicle, UAV, tracker”, step 805, for generatingso-called “UAV tracks”, step 807, which is further described inconnection with FIGS. 11 and 14. The plots with regular Doppler velocityprofile may be fed to a so called “Bird tracker”, step 806, forgenerating so-called “Bird tracks”, step 807, which is further describedin connection with FIGS. 12 and 13. Plots with irregular Dopplervelocity, which does not fit into any UAV tracks 807 may be send to thebird tracker 806 to see, if the plots fits into any bird tracks 808. Theobtained UAV tracks 807 and bird tracks 808 may go through aclassification process, step 809, resulting in classified tracks, step810. An example of a classification process is further described inconnection with FIG. 15.

FIG. 9 is a flow diagram illustrating generation of full type radarplots holding range, azimuth radial velocity and return energyinformation according to an example embodiment. The diagram of FIG. 9corresponds to step 801 of FIG. 8, in which plots are combined into fulldata type plots. The received range-Doppler velocity plots, 608, andrange-azimuth plots, 704, all hold range data, and in step 801 a, therange data of range-azimuth plots is compared with the range data ofrange-Doppler velocity plots. The plots having matching range data,where there may be a maximum threshold difference in range for definingmatching plots, are combined into full data type plots, step 801 c,while in step 801 b the azimuth-range plots having no range match with arange-Doppler velocity plot are forwarded to the bird tracker andrange-Doppler velocity plots having no range match with a range-azimuthplot are discarded. Each combined plot now holds the following data froma number of hit range cells: energy of return signal(s), range, azimuth,and radial velocity/velocities. Also for the combined plots, it ispreferred that in order to form at plot, there needs to be at leastfour, five or six neighboring range cells having matching data.

The resulting combined plots of step 801 c may then be divided based onDoppler velocity profiles, step 802, as described in connection withFIG. 10, which is a flow diagram illustrating division of obtained fulltype radar plots into regular and irregular plots based on velocityinformation. As illustrated and described in connection with FIGS. 4aand 4b , then for each range cell, the range-Doppler matrix holds aDoppler signature with a number of bins covering the radial velocityspan being covered by the scanning radar system 101. A combined plot mayrepresent data from one or more neighboring range cells, having one ormore corresponding neighboring Doppler signatures, and the Dopplersignatures may represent radial velocities within a radial velocityspan, which may include both positive and negative radial velocities.

Thus, the first step in dividing the combined plots is to analyse theradial or Doppler velocity data of the plots. This is done in step 802a, and if a plot holds data representing only positive or only negativevelocities, the plot is stored as a plot with regular Doppler velocityprofile, step 804. If the plot holds data representing both positive andnegative velocities, then it is determined if the difference in maximumand minimum velocities, i.e. the difference between the most positiveradial velocity and the most negative radial velocity, is larger than orequal to a predetermined minimum velocity difference of delta velocity.If the difference in maximum and minimum radial velocities is below thepredetermined minimum velocity difference, then the plot is stored as aplot with regular Doppler velocity profile, step 804, while if thedifference in maximum and minimum radial velocities is equal to or abovethe predetermined minimum velocity difference, then the plot is storedas a plot with irregular Doppler velocity profile, step 803.

The predetermined minimum velocity difference between the most positiveradial velocity and the most negative radial velocity may be selected tobe at least 50%, such as at least 60%, such as at least 70%, or such asat least 75% of the total radial velocity span being covered by thescanning radar system 101. In an embodiment, the FMCW radar system 101is configured to provide scan data indicative of radial velocitieswithin the range of minus 30 m/s to plus 30 m/s, and here thepredetermined minimum velocity difference between the most positiveradial velocity and the most negative radial velocity may be set to beat least 45 m/s.

FIG. 11 is an overview flow diagram illustrating generation of UnmannedAerial Vehicle, UAV, tracks according to an example embodiment. Thediagram of FIG. 11 corresponds to the UAV tracker, step 805, of FIG. 8.The tracking process 805 is based on the plots with irregular Dopplervelocity profile found in step 803. The first step is to analyse if aplot matches any existing UAV tracks, step 805 a. If no tracks has beengenerated yet, or if there is no match, the plot is stored and may beused for generating a new UAV track, step 805 b. If the plot gets tooold without having a match with other plots to form a track, the storedplot may be discarded and may be fed into the bird tracker, step 806. Ifthere are several stored plots having a match, such as at least two orthree, but preferably at least four, five or six matching plots, a newUAV track may be generated, step 805 c, and stored as a UAV track, step807. The stored UAV tracks are used in step 805 a when matching a newplot with an existing UAV track, and if there is a match, the matchingUAV track is updated with the data of the new plot, step 805 d. Thegenerated and stored UAV tracks, 807, may then be classified, step 809,as further described in connection with FIG. 15. In order to form aplot, there need to be at least two neighboring range cells havingmatching data, but it is preferred that in order to form at plot, thereneeds to be at least 4, 5 or 6 neighboring range cells having matchingdata.

FIG. 12 is an overview flow diagram illustrating generation of birdtracks according to an example embodiment. The diagram of FIG. 12corresponds to the bird tracker, step 806, of FIG. 8. The trackingprocess 806 is based on the plots with regular Doppler velocity profilefrom step 804 and the plots with no Doppler velocity profile from steps801 and 804, but may also include the plots being discarded from the UAVtracker, step 805 b. The first step is to analyse if a plot matches anyexisting bird tracks, step 806 a. If no tracks has been generated yet,or if there is no match, the plot is stored and may be used forgenerating a new bird track, step 806 b. If the plot gets too oldwithout having a match with other plots to form a track, the stored plotmay be discarded. In step 806 e it is examined whether the discardedplot is a discarded UAV plot or not; if no, the plot is finallydiscarded or dropped, step 806 f, if yes, the plot may be forwarded tothe classifier, 809. If there are several stored plots having a match,such as at least two or three, but preferably at least four, five or sixmatching plots, a new bird track may be generated, step 806 c, andstored as a bird track, step 808. The stored bird tracks are used instep 806 a when matching a new plot with an existing bird track, and ifthere is a match, the matching bird track is updated with the data ofthe new plot, step 806 d. The generated and stored bird tracks, 808, maythen be classified, step 809, as further described in connection withFIG. 15.

Examples of matching conditions are known in the art of radar scanningand track generation, but a match condition may have to be fulfilled fora set of data, which are part of the plots being compared, when a newtrack is generated based on a number plots, while the data of a new plothas to match corresponding data of a stored track, when a new plot isused for updating an existing track. A match condition may be fulfilledfor corresponding plot or track data, when the difference between thedata being matched is below a predetermined threshold difference. Thisis further describe in connection with FIG. 13 for bird tracks and FIG.14 for UAV tracks.

FIG. 13 is a detailed flow diagram illustrating generation of birdtracks. The diagram of FIG. 13 corresponds to the bird tracker, step806, of FIG. 8, and is a more detailed example of the bird trackingprocess of FIG. 12. Thus, the tracking process 806 is based on the plotswith regular Doppler velocity profile and/or plots having no Dopplervelocity profile found in step 804, and may also include the plots beingdiscarded from the UAV tracker, step 805 b. The first step is to analyseif a plot matches any existing bird tracks, step 806 a. If there are anyexisting bird tracks, a number of data has to match: the position of theobject being tracked has to match with the position of the object of thenew plot, step 806 aa, where the position may be based on range andazimuth data; the movement direction of the object being tracked has tomatch with the movement direction of the object of the new plot, step806 ab, where the movement direction of the track is based on theposition of several plots, and the movement direction of the new plotmeans that the position of the new plot shall match the movementdirection given in the track; the speed and Doppler radial velocity ofthe object being tracked have to match with the speed and Doppler radialvelocity of the object of the new plot, step 806 ac, where the speed ofthe track is based on changes in the position of several plots, and thespeed of the new plot means that the position of the new plot shallmatch the speed and movement direction given in the track; the size ofthe object being tracked has to match with the size of the object of thenew plot, step 806 ad, where the object size may be based on a summationof the energy of return signals within a plot. If a new plot fulfils allthe matching step, the matching bird track is updated with the data ofthe new plot, step 806 d.

If no tracks has been generated yet, or if there is no match, the newplot is stored and may be used for generating a new bird track, step 806b. If the plot gets too old, i.e. being older than a given maximum timeT, without having a match with other plots to form a track, the storedplot may be discarded. In step 806 e it is examined whether thediscarded plot is a discarded UAV plot or not; if no, the plot isfinally discarded or dropped, step 806 f, if yes, the plot may be to theclassifier, 809. When several stored plots which are not too old havebeen obtained, these plots are examined to see if the number of matchingconditions can be fulfilled to generate a new track. The matchingconditions for plots to form a new tack may be similar the matchingconditions for a new plot and an existing track: the position of theobject of the plots has to match with each other, step 806 ba, whereposition may be based on range and azimuth data; the movement directionof the objects of the plots has to match, step 806 bb, where themovement direction is based on the position of the objects of severalplots; the speed and Doppler radial velocity of the objects of the plotshave to match, step 806 bc, where the speed of the objects is based onchanges in the object position of several plots; the size of the objectof the plots has to match, step 806 bd, where the object size may bebased on a summation of the energy of return signals within a plot. Ifthere are several stored plots having a match, such as at least two orthree, but preferably at least four, five or six matching plots, a newbird track may be generated, step 806 c, and stored as a bird track,step 808. The stored bird tracks are used in step 806 a when matching anew plot with an existing bird track. The generated and stored birdtracks, 808, may then be classified, step 809, as further described inconnection with FIG. 15.

FIG. 14 is a detailed flow diagram illustrating generation of UnmannedAerial Vehicle, UAV, tracks. The diagram of FIG. 14 corresponds to theUAV tracker, step 805, of FIG. 8, and is a more detailed example of theUAV tracking process of FIG. 11. Thus, the tracking process 805 is basedon the plots with irregular Doppler velocity profile found in step 803.

The first step is to analyse if a plot matches any existing UAV tracks,step 805 a. If there are any existing UAV tracks, a number of data hasto match: the Doppler radial velocity of the object being tracked has tomatch with the Doppler radial velocity of the object of the new plot,step 805 aa; the position of the object being tracked has to match withthe position of the object of the new plot, step 805 ab, where positionmay be based on range and azimuth data; the size of the object beingtracked has to match with the size of the object of the new plot, step805 ac, where the object size may be based on a summation of the energyof return signals within a plot. If a new plot fulfils all the matchingstep, the matching UAV track is updated with the data of the new plot,step 805 d.

If no tracks has been generated yet, or if there is no match, the newplot is stored and may be used for generating a new UAV track, step 805b. If the plot gets too old, i.e. being older than a given maximum timeT, without having a match with other plots to form a track, the storedplot may be discarded, step 805 bd. A discarded UAV plot may then besend to the bird tracker, step 806, to see if the plot fits into a birdtrack. When several stored plots which are not too old have beenobtained, these plots are examined to see if the number of matchingconditions can be fulfilled to generate a new track. The matchingconditions for plots to form a new tack may be similar the matchingconditions for a new plot and an existing track: the Doppler radialvelocity of the objects of the plots has to match, step 805 ba; theposition of the objects of the plots has to match, step 805 bb, whereposition may be based on range and azimuth data; the size of the objectsof the plots has to match, step 805 bc, where the object size may bebased on a summation of the energy of return signals within a plot. Ifthere are several stored plots having a match, such as at least two orthree, but preferably at least four, five or six matching plots, a newUAV track may be generated, step 805 c, and stored as a UAV track, step807. The stored UAV tracks are used in step 805 a when matching a newplot with an existing UAV track. The generated and stored UAV tracks,807, may then be classified, step 809, as further described inconnection with FIGS. 15 and 16.

An important aspect of the present invention is to provide data, whichcan be used for tracking and classification of UAVs or UAV like objects.Thus, the tracking of birds or bird like objects and also theclassification of bird or bird like objects, may be optional for thesystems and methods of the present disclosure. It is noted that all theobjects being tracked by a UAV track has both positive and negativeradial or Doppler velocities, which for example may indicate that atracked object has one or more propeller blades; however flying objectswith propeller blades may have very different sizes, where a UAV, whichis unmanned, may have a rather small size and thereby a low energy oramplitude in the returned radar signals, while a manned helicopter willhave a much higher energy or amplitude in the returned radar signals.

For objects tracked by a UAV track, the received reflected energiesrepresent a radial velocity span from an outer negative velocity to anouter positive velocity with most of the reflected energy representingradial velocities close to the center of the velocity span. This isillustrated in FIG. 16, which holds an energy curve 1600 illustratingreflected energy in dB as a function of radial velocity or Dopplervelocity. The curve 1600 is based on the sum of return energies of rangecells or bins of the Doppler signatures from plots forming a UAV track,where the range cells or bins have return energy data for differentradial/Doppler velocities. The curve 1600 has a center part 1601representing the highest amount of energy, which for this embodiment iscentered around a slightly positive Doppler velocity. The center part1601 represents return energies, which may correspond to a center bodyof a UAV. The curve 1601 also has a negative outer energy part 1602 anda positive outer energy part 1603. The outer energy parts 1602 and 1603represent return energy within the so-called micro-Doppler range, andmay correspond to energy being reflected from propeller blades of a UAV.

For the curve 1601, the boundary between the center part 1601 and theouter energy parts 1602 and 1603 is set at limiting velocities 1604 and1605. For the embodiment illustrated in FIG. 16, the energy level of thecenter part 1601 decreases to a minimum on both sides of the maximumenergy velocity, and then the energy slowly starts increasing again. Thelimiting velocities 1604, 1605 are selected as the velocities where theenergy has increased by 3 dB from the minimum energy.

For a flying object, such as a UAV, the micro-Doppler signals must havea certain strength compared to the strength of the center body signalsin order for the propeller blades to keep the UAV flying. In FIG. 16,the strength of the micro-Doppler signals is represented by the sum ofenergies within the outer energy parts 1602 and 1603, and the strengthof the center body signals is represented by the sum of energies withinthe center part 1601. Thus, in order to classify an object of a UAVtrack as a UAV, the strength of the outer Doppler velocity signalsshould be above a certain or predetermined fraction of the strength ofthe center Doppler velocity signals. Here, the strength of the outerDoppler velocity signals may be no less than 1/1000 of the strength ofthe center Doppler velocity signals, or the strength of the outerDoppler velocity signals should not be more than 30 dB weaker than thestrength of the center Doppler velocity signals.

As mentioned above, flying objects of a UAV track may vary in size,where a manned helicopter will have a much higher energy or amplitude inthe returned radar signals. Thus, if the total strength of the receivedDoppler velocity signals as represented by the sum of return energiesfor all Doppler velocity signals, which for the curve 1600 of FIG. 16would be the total sum of the energies of the center part 1601 and theenergies of the outer parts 1602 and 1603, is above a certain orpredetermined maximum, the object track may be classified as a non-UAVtrack. Here, if the total sum of return energies represents an objecthaving a radar cross-section, RSC, above 1 m², the track may beclassified as a non-UAV track.

FIG. 15 is a flow diagram illustrating classification of obtained tracksaccording to an example embodiment. FIG. 15 illustrates classification,809, of detected objects being part of UAV tracks, 807, and of detectedobjects being part of bird tracks, 808, where the classification of birdor bird like objects, may be optional. The first step, step 809 a, inthe process of the classification of UAV tracks may be to determine thesum of return energies for range cells representing Doppler velocitieswithin a center range of the observed velocity range, and to determinethe sum of return energies for range cells representing positive andnegative Doppler velocities within the outer ranges of the observedvelocity range. Step 809 a may also comprise determining the total sumof return energies of range cells for all Doppler velocity signals,which sum of return energies represents a total body mass with acorresponding radar cross-section.

The next step, step 809 b, is then to determine, if the summed outervelocity energy is above a predetermined fraction of the summed centervelocity energy. Alternatively, it may be determined if the summed outervelocity energy is above a predetermined fraction of the total summedvelocity energy. If no, the track is classified as a non-UAV track, step809 d, and if yes, the track may be a UAV track. However, in step 809 b,it is also determined if the total summed velocity energy is below orequal to a summed energy representing a total body mass with apredetermined maximum radar cross-section. If no, the track isclassified as a non-UAV track, step 809 d, and if yes, the track may beclassified as a UAV track, if there is also a yes to the requirements tothe summed outer velocity energy, step 809 c.

For the present embodiment, the tracks are classified by the computersystem 102, from where the classified tracks are forwarded by livestreaming to the command and control system 103, where the classifiedtracks may be displayed in real time, 810 a, and then stored in adatabase, step 810 b.

Thus, an important result of the radar scanning processes describedherein, is the display in real time of the generated and classified UAVtracks at the command and control system 103. Based on information ofthe displayed tracks, the people at the command and control center havethe possibility to decide if any actions are needed against any detectedUAV.

A major difference in radar based scanning of birds and UAVs is that avery high number of bird plots, here regular Doppler velocity profileplots, such as up to 1000 to 5000 plots, may be generated, while onlyvery few UAV plots, here irregular Doppler velocity profile plots, suchas two, four or six plots, may be generated. Thus, only a single or veryfew UAV objects may be tracked, while many more birds or flocks of birdmay have to be tracked and distinguished from each other, whereby thebird tracking and classification needs to more precise and thereforebased on a higher number of variables than the UAV tracking andclassification, where for the UAV tracking the radial or Dopplervelocity profiles give the most important information.

The first step in the process of the classification of bird tracks maytherefore be to determine further parameters based on data of obtainedtracks, as illustrated in step 809 aa. Here, the total object mass anddistribution of the object mass is determined from energy of returnsignal(s) from plot data, where the mass distribution may be determinedbased on the return energy data of the bins of the Doppler signatures ofa plot. Furthermore, speed, direction, acceleration, and sinuosity ofthe movement curve may be determined from the object track data.

Based on the obtained results determined from a track and thecorresponding plots, the track can be classified as a bird track, or asa non-bird track, step 809 cc. Here, a non-bird object may be anaeroplane, which has a much bigger size and object mass, and which canhave a higher speed and better sinuosity than a bird or flock of birds.For tracks classified as bird tracks, then based on results determinedfrom the plots and track data, the track may be classified as a smallbird track, a medium bird track, a large bird track, or a flock of birdstracks. Here, the size or object mass may be used to classify a bird assmall, medium, or large, while sinuosity or lack of sinuosity may be agood parameter classifying the object as a flock of birds. For systemsincluding bird tracking and classification, the classified bird tracksmay be forwarded by live streaming to the command and control system103, where the classified tracks may be displayed in real time, 810 a,and then stored in a database, step 810 b.

It is noted that a discarded UAV plot, which has not be matched with anybird tracks, 806 e, may be classified as a track in itself, which can bea so-called “hovering UAV track”, which may also be forwarded by livestreaming to the command and control system 103, where the classifiedtracks may be displayed in real time, 810 a, and then stored in adatabase, step 810 b.

The foregoing description in connection with FIGS. 1 to 16 has dealtwith a FMCW radar scanning system for detecting objects, and proceduresor methods for generating radar plots and tracks based on obtained scandata. The generation of tracks includes generation of tracks qualifyingas Unmanned Aerial Vehicle, UAV, tracks, and procedures are alsodescribed for classifying a generated UAV track as a real UAV track.

It is, however, within embodiments of the present disclosure to providea system, which is able to detect and track UAVs, and which further isable to distinguish between known and unknown UAVs. Such a system mayalso be configured to control operation of a known UAV based on obtainedtracking information of an unknown UAV. Such as system is shown in FIG.17, which is a schematic block diagram illustrating the basic structureof an Unmanned Aerial Vehicle, UAV, system according to an exampleembodiment.

The system of FIG. 17 holds a FMCW scanning radar system 101electronically connected to a computer system 102, which are equal tothe radar and computer systems 101 and 102 of FIG. 1a . Generated outputdata from the computer system 102 is communicated to an external commandand control system or station 103, which is also shown in FIG. 1a . Thesystem of FIG. 17 further comprises a known, first co-operating UnmannedAerial Vehicle, UAV, 1701 and an antenna 1705. The co-operating UAV 1701is provided with a telemetric transmitter/receiver 1702 for exchangingtelemetric radio frequency, RF, data with the antenna 1705, which isfurther in data communication with the command and control station 103,whereby the flight path of the co-operating UAV 1701 can be controlledfrom the command and control station 103. The co-operating UAV 1701 alsoholds a camera 1704, such as a video camera, whereby live video signalscan be transmitted from the UAV 1701 via the antenna 1705 to the commandand control station 103. The co-operating UAV 1701 may also be providedwith a transponder 1703 holding identification information, ID, for theUAV 1701, whereby transponder data holding the identificationinformation may be forwarded from the UAV 1701 to the command andcontrol station 103. The co-operating UAV 1701 may also hold a globalpositioning system, GPS, which is not shown in FIG. 17, and thetelemetric data forwarded to the command and control station 103 mayhold position data obtained from the GPS system.

In FIG. 17, the co-operating UAV 1701 is exposed to radar signals fromthe radar system 101 and thereby detected by the radar system 101. FIG.17 also shows a second Unmanned Aerial Vehicle, UAV, 105, which in thiscase is an unknown or non-co-operating UAV, 105, which is not intelemetric communication with the command and control system 103. Thus,radar scan data are obtained by the radar system 101 for both the firstUAV 1701 and the second UAV 105, which scan data may be processed byprocessing circuitry of the computer system 102 to obtain radar plotsand object tracks for the detected UAVs 105 and 1701. Furthermore, thecommand and control system 103 receives the telemetric data and possiblealso transponder data from the first UAV 1701, which can be forwarded tothe computer system 102 and compared with the obtained UAV track data.The final result of such a comparison may be a classification of theobtained UAV tracks, to thereby make a distinction between a track of aknown, co-operating UAV, and a track of an unknown, non-co-operatingUAV. The classified UAV tracks may be forwarded and displayed in realtime at the command and control system 103.

Based on information of the displayed tracks, the people at the commandand control center station 103 have the possibility to decide if anyactions are needed against any detected UAV, and flight path commandsand possible also action commands may be forwarded via telemetriccommunication to the known, co-operating UAV 1701, which may adapt itsflight path accordingly and execute any received action commandsaccordingly.

The formation and classification of UAV tracks for known and unknownUAVs is illustrated in FIGS. 18 and 19, for which FIG. 18 is an overviewflow diagram illustrating processing steps including plot generation,track generation and classification of a detected object based on dataobtained by the system of FIG. 17 according to an example embodiment.The first part of the steps of FIG. 18 follows the first part of thesteps of FIG. 8, which again refers to the generation of plot inputdata, step 500, from FIG. 5, the generation of range-Doppler velocityplots, steps 600 and 607, from FIG. 6, and the generation ofrange-azimuth plots, steps 700 and 703, from FIG. 7.

From the obtained range-Doppler velocity plots, 703, and the obtainedrange-azimuth plots, 703, the process proceeds by comparing andcombining the obtained plots, 608 and 704, into full data type plots,step 801, which is further described in connection with FIG. 9. It isnoted that during the following circular radar scan, new range-Dopplerplots are generated and stored during the scan, while new range-azimuthplots are first generated and stored when the following circular radarscan is completed. This procedure of plot generation is repeated foreach full circular radar scan.

When comparing the obtained range-Doppler velocity plots andrange-azimuth plots at step 801 in FIG. 8, the range-azimuth plots,which cannot be matched with a range-Doppler velocity plot, is forwardedto a so called “Bird tracker” 806 via step 804. The range-Dopplervelocity plots, which cannot be matched with a range-azimuth plot isdiscarded. However, for the processing steps of FIG. 18, we only need tolook at plots qualifying for the generation UAV tracks, so for step 801the range-azimuth plots, which cannot be matched with a range-Dopplervelocity plot may be forwarded to a “Bird tracker” or may be discardedtogether with the range-Doppler velocity plots, which cannot be matchedwith a range-azimuth plot.

The remaining plots in step 801 are combined into full data type plots,which now hold range, azimuth, radial velocity, and return energy datafor detected objects forming part of a plot. The next step is to selectthe full data type plots qualifying for the generation of UAV tracks,and this selection is based on Doppler velocity profile, step 802, whichis further described in connection with FIG. 10. The combined plot,which are selected as qualifying for the generation of UAV tracks, arethe plots with irregular Doppler velocity profile, step 803, whereirregular type radar plots have velocity data representing positive andnegative radial velocities within an observed radial velocity range. Theselected irregular type radar plots may have velocity data representingpositive and negative radial velocities with at least a predeterminedminimum velocity difference between the most positive radial velocityand the most negative radial velocity.

The plots with irregular Doppler velocity profile are fed to a so called“Unmanned Aerial Vehicle, UAV, tracker”, step 1805, for generatingso-called “UAV tracks”, step 1807, which is further described inconnection with FIG. 19. In step 1805, a UAV track is formed based on atleast two matching plots with irregular Doppler profile. However, theUAV tracker, step 1805, also receives telemetric data, if any, step1812, and transponder data, if any, step 1813, which telemetric andtransponder data may originate from a known UAV. Any received UAVtelemetric and transponder data are stored together with the UAV trackdata, step 1807.

The obtained UAV tracks 1807 now go through a classification process,step 1809, resulting in classified real UAV tracks. An example of aclassification process, which may be used in step 1809 for classifying aUAV track as a real UAV track, is described in connection with FIG. 15.The UAV track being classified as real UAV tracks are now furtherclassified as representing a first, known or co-operating UAV, step1810, or representing a second, unknown or non-co-operating UAV, step1811. The real UAV tracks having a match between corresponding trackdata and received telemetric and/or transponder data, are classified asco-operating UAV tracks, step 1810, and real UAV tracks having no matchbetween corresponding track data and received telemetric and/ortransponder data, are classified as non-co-operating UAV tracks, step1811.

FIG. 19 is an overview flow diagram illustrating generation of UnmannedAerial Vehicle, UAV, tracks based on data obtained by the system of FIG.17 according to an example embodiment. The diagram of FIG. 19corresponds to the UAV tracker 1805 of FIG. 18, and may hold the samesteps as described in connection with the UAV tracker 805 of FIG. 11.The main difference being that the UAV tracker, 1805, of FIGS. 18 and 19also receives telemetric data, if any, step 1812, and transponder data,if any, step 1813, which telemetric and transponder data may originatefrom a known UAV.

Thus, the tracking process 1805 is based on the plots with irregularDoppler velocity profile found in step 803. The first step is to analyseif a plot matches any existing UAV tracks, step 1805 a. If no tracks hasbeen generated yet, or if there is no match, the plot is stored and maybe used for generating a new UAV track, step 1805 b. If the plot getstoo old without having a match with other plots to form a track, thestored plot may be discarded or may be fed into the bird tracker, step806. If there are several stored plots having a match, such as at leasttwo or three, but preferably at least four, five or six matching plots,a new UAV track may be generated, step 1805 c, and stored as a UAVtrack, step 1807. The stored UAV tracks are used in step 1805 a whenmatching a new plot with an existing UAV track, and if there is a match,the matching UAV track is updated with the data of the new plot, step1805 d. It is also in steps 1805 a and 1805 d that received telemetricdata and/or transponder data are matched with the data of the generatedUAV tracks, and then stored together with the data of the matchingtracks at step 1807. The generated and stored UAV tracks, 1807, may thenbe classified a real or non-real UAV tracks, step 1809, and furtherclassified as representing a first, known or co-operating UAV, step 1810of FIG. 18, or representing a second, unknown or non-co-operating UAV,step 1811 of FIG. 18.

When matching plots with irregular Doppler velocity profile in order togenerate a UAV track, 1805 c, or match a plot to an existing UAV track,1805 a, the matching may comprise to determine if there is a matchbetween radial velocity data, range data, and return energy data. Thematching of return energy data of two irregular type radar plots may bebased on a total sum of return energies representing all radial velocitysignals for each of the two irregular type radar plots being matched,and/or the based on a sum of center return energies corresponding to acentered radial velocity span within the observed radial velocity rangefor each of the two irregular type radar plots being matched. A matchcondition may be fulfilled for a set of corresponding data if thedifference between the data is equal to or below a predeterminedthreshold difference.

When matching the received telemetric data and/or transponder data withthe data of the generated UAV tracks, steps 1805 a and 1805 d,predetermined matching conditions may have to be fulfilled between dataof the stored tracks and the received telemetric data and/or transponderdata. Here, the matching conditions may comprise a match betweenposition data, a match between velocity data and/or a match between sizedata. Also here, a match condition may be fulfilled for a set ofcorresponding data if the difference between the data is equal to orbelow a predetermined threshold difference.

FIG. 20 is a block diagram illustrating exchange of signals betweenparts of the system of FIG. 17 according to an example embodiment. Theradar system 101 provides scan data which is processed by the computersystem 102 into UAV tracks. The command and control station 103 receivestelemetric data and/or transponder data from the first, co-operatingUAV, which may further be forwarded to the computer system 102, whichthen classify the obtained UAV tracks into co-operating UAV tracks andnon-co-operating UAV tracks, step 2001. Track data for the classifiedtracks is then forwarded to the command and control station 103.

From the received track data, the command and control station 103determines whether there is any second, non-co-operating UAV tracks,step 2002. If yes, the command and control station 103 starts generatingand forwarding flight plan commands, step 2003, to the firstco-operating UAV 1701 based on object data from the object track of thesecond non-co-operating UAV 105 and based on telemetric data and/ortransponder data received from the first co-operating UAV 1701, step2007. The first co-operating UAV 1701 receives the flight path commandsas indicated by step 2008.

The first co-operating UAV 1701 holds a camera 1704, and the telemetricdata received by the command and control station 103 including a videosignal. Based on the received telemetric data, the command and controlstation 103 determines whether the second non-co-operating UAV 105 is invideo sight of the first co-operating UAV 1701, step 2004. If yes, thecommand and control station 103 starts generating and forwarding flightplan commands to the first co-operating UAV 1701 based on the receivedtelemetric video signal, step 2005.

It is within an embodiment that the command and control station 103 isconfigured to generate and forward the flight plan commands based onposition data obtained from the object track of the second nonco-operating UAV 105, step 2003, until the second non co-operating UAV105 is detected within the received video signal, step 2005. At thispoint in time, the command and control station 103 may be configured togenerate and forward the flight plan commands based on the receivedvideo signal only.

When the UAV of a UAV object track is classified as a secondnon-co-operating UAV 105, it is within an embodiment that the commandand control circuitry 103 is configured to generate and forward actioncommands to the first UAV 1701 based on information obtained from theobject track of the second UAV 105, steps 2006 and 2009. The actioncommands may also be at least partly based on the received telemetricdata and/or transponder data for the first co-operating UAV 1701. Thefirst co-operating UAV 1701 may then be configured to execute an action,step 2010, based on the action commands received from the command andcontrol station 103. The execution of the action may also be based onreceived flight path commands.

According to an embodiment the action and flight path commands maycomprise a flight disturbing action command, whereby the firstco-operating UAV 1701 is configured to execute a flight-route or flightplan disturbing action for the second non co-operating UAV 105. Here,the flight-route or flight plan disturbing action to be executed may beto divert the first co-operating UAV 1701 towards the second nonco-operating UAV 105 to induce a collision between the first and secondUAVs, 1701, 105.

The command and control station 103 may generate the flight planinformation and/or action information based on position, velocity and/orsize data obtained from the object track of the second non-co-operatingUAV 105. Here, the position data may include range and azimuth relativeto the radar system, and the velocity data may include the radialvelocity relative to the radar system. The size data may be determinedbased on energy of return scan signals within plots forming the objecttrack of the second non-co-operating UAV 105.

The invention has been described in conjunction with various embodimentsherein. However, other variations to the disclosed embodiments can beunderstood and effected by those skilled in the art in practicing theclaimed invention, from a study of the drawings, the disclosure, and theappended claims. In the claims, the word “comprising” does not excludeother elements or steps, and the indefinite article “a” or “an” does notexclude a plurality.

The invention claimed is:
 1. A Frequency Modulated Continuous Wave,FMCW, radar system comprising: one or more antennas configured totransmit and receive FMCW radar wave signals for scanning for objects,such as unmanned aerial vehicles, UAVs, within a full circular detectioncoverage range; and processing circuitry configured to: provide scandata based on transmitted and received FMCW radar signals and azimuthposition of the antenna(s), said scan data representing range cellswithin image lines of circular radar images, where each radar imageholds a number of image lines defining a full circular radar image, witheach image line corresponding to an azimuth orientation, and where eachimage line holds a number of range cells, with each range cellcorresponding to a distance to the radar antenna(s) and wherein anobject, which is detected within an azimuth orientation and range to theradar antenna(s), is represented by a number of hit range cells in oneor more image lines, and wherein each hit range cell holds data forenergy of returned signal(s) and data for radial velocity or velocitiesbased on Doppler frequency signals, said scan data thereby for each hitrange cell holding information of range, azimuth orientation, energy ofreturned radar wave signals, and radial velocity or velocities of adetected object; and generate full data type radar plots based onobtained scan data, each said full data type radar plot holding azimuth,range, radial velocity and received return energy data for one or moredetected objects; characterized in that the processing circuitry isfurther configured to: select irregular type radar plots from full datatype radar plots, said irregular type radar plots having velocity datarepresenting both positive and negative radial velocities within anobserved radial velocity range, and said irregular type radar plotshaving at least a predetermined minimum velocity difference between theobserved radial velocity with the largest positive value and theobserved radial velocity with the largest absolute negative value; andto generate one or more object tracks or unmanned aerial vehicle, UAV,tracks, where each object/UAV track is based on at least two irregulartype radar plots having a match between corresponding data of said atleast two irregular type radar plots.
 2. A FMCW radar system accordingto claim 1, wherein the system is configured to provide scan dataindicative of radial velocities within a predetermined positive velocityrange and a predetermined negative velocity range of same size as thepredetermined positive velocity range, and wherein the predeterminedminimum velocity difference between the observed radial velocity withthe largest positive value and the observed radial velocity with thelargest absolute negative value is at least 50% the combinedpredetermined positive and negative velocity ranges.
 3. A FMCW radarsystem according to claim 2, wherein the system is configured to providescan data indicative of relative velocities within the range of −30 to+30 m/s, and wherein the predetermined minimum velocity differencebetween the observed radial velocity with the largest positive value andthe observed radial velocity with the largest absolute value is at least45 m/s.
 4. A FMCW radar system according to claim 1, wherein said matchbetween corresponding data comprises a match between radial velocitydata, a match between range data, and/or a match between return energydata.
 5. A FMCW radar system according to claim 1, wherein theprocessing circuitry is configured to: determine for the plots of agenerated object/UAV track: an outer energy sum being the sum of returnenergies for range cells representing positive and negative radialvelocity signals within outer velocity ranges of the observed radialvelocity range; a center energy sum being the sum of return energies forrange cells representing radial velocity signals within a center rangeof the observed radial velocity range, and/or a total energy sum beingthe total sum of return energies of range cells representing all radialvelocity signals of the observed radial velocity range; and wherein theprocessing circuitry is further configured to: classify the object/UAVtrack as a real UAV track or non-real UAV track based at least partly ona comparison of the determined outer energy sum with the determinedcenter energy sum and/or with the determined total energy sum.
 6. A FMCWradar system according to claim 5, wherein the processing circuitry isconfigured to: classify the object/UAV track as a non-real UAV trackwhen the determined outer energy sum is below a predetermined fractionof the determined center energy sum, wherein the predetermined fractionof the determined center energy sum is 1/1000.
 7. A FMCW radar systemaccording to claim 5, wherein the processing circuitry is configured to:classify the object/UAV track as a non-real UAV track when thedetermined outer energy sum is below a predetermined fraction of thedetermined total energy sum.
 8. A FMCW radar system according to claim5, wherein the processing circuitry is configured to: classify theobject/UAV track as a real UAV track or non-real UAV track based atleast partly on a comparison of the determined total energy sum with apredetermined maximum energy representing a predetermined maximum radarcross-section.
 9. A FMCW radar system according to claim 5, wherein theprocessing circuitry is configured to: classify the object/UAV track asa non-UAV or large UAV track when the determined total energy sum isabove a predetermined maximum energy representing a predeterminedmaximum radar cross-section, wherein the predetermined maximum radarcross-section is 1 m².
 10. A FMCW radar system according to claim 5,wherein the processing circuitry is configured to: classify theobject/UAV track as a real UAV track when the determined outer energysum is above a predetermined fraction of the determined center energysum and/or above a predetermined fraction of the determined total energysum, and when the determined total energy sum is below a predeterminedmaximum energy representing a predetermined maximum radar cross-section.11. A FMCW radar system according to claim 1, wherein the processingcircuitry is configured to: generate full data type radar plots based ongrouping of neighboring hit range cells within one or more image linesof a full circular radar image having matching range, azimuth and radialvelocity data.
 12. A Frequency Modulated Continuous Wave, FMCW, radarsystem comprising: one or more antennas configured to transmit andreceive FMCW radar wave signals for scanning for objects, such asunmanned aerial vehicles, UAVs, within a full circular detectioncoverage range; and processing circuitry configured to: provide scandata based on transmitted and received FMCW radar signals and azimuthposition of the antenna(s), said scan data representing range cellswithin image lines of circular radar images, where each radar imageholds a number of image lines defining a full circular radar image, witheach image line corresponding to an azimuth orientation, and where eachimage line holds a number of range cells, with each range cellcorresponding to a distance to the radar antenna(s), and wherein anobject, which is detected within an azimuth orientation and range to theradar antenna(s), is represented by a number of hit range cells in oneor more image lines, and wherein each hit range cell holds data forenergy of returned signal(s) and data for radial velocity or velocitiesbased on Doppler frequency signals, said scan data thereby for each hitrange cell holding information of range, azimuth orientation, energy ofreturned radar wave signals, and radial velocity or velocities of adetected object; characterized in that the processing circuitry isfurther configured to: generate full data type radar plots based onobtained range cell scan data, each said full data type radar plotholding azimuth, range, radial velocity and received return energy datafor one or more detected objects; select irregular type radar plots fromfull data type radar plots, said irregular type radar plots havingvelocity data representing both positive and negative radial velocitieswithin an observed radial velocity range; generate one or more objecttracks or unmanned aerial vehicle, UAV, tracks, where each object/UAVtrack is based on at least two irregular type radar plots having a matchbetween corresponding data of said at least two irregular type radarplots; determine for the plots of a generated object/UAV track: an outerenergy sum being the sum of return energies for range cells representingpositive and negative radial velocity signals within a first and asecond outer velocity range outside a center range of the observedradial velocity range; a center energy sum being the sum of returnenergies for range cells representing radial velocity signals within thecenter range of the observed radial velocity range, and/or a totalenergy sum being the total sum of return energies of range cellsrepresenting all radial velocity signals of the observed radial velocityrange; and wherein the processing circuitry is further configured to:classify the object/UAV track as a real UAV track or non-real UAV trackbased at least partly on a comparison of the determined outer energy sumwith the determined center energy sum and/or with the determined totalenergy sum.
 13. A FMCW radar system according to claim 12, wherein theprocessing circuitry is configured to: classify the object/UAV track asa real UAV track or non-real UAV track based at least partly on acomparison of the determined total energy sum with a predeterminedmaximum energy representing a predetermined maximum radar cross-section.14. A FMCW radar system according to claim 12, wherein the processingcircuitry is configured to: classify the object/UAV track as a real UAVtrack when the determined outer energy sum is above a predeterminedfraction of the determined center energy sum and/or above apredetermined fraction of the determined total energy sum, and when thedetermined total energy sum is below a predetermined maximum energyrepresenting a predetermined maximum radar cross-section.
 15. A FMCWradar system according to claim 12, wherein the processing circuitry isconfigured to: classify the object/UAV track as non-real UAV track whenthe determined outer energy sum is below a predetermined fraction of thedetermined center energy sum, wherein the predetermined fraction of thedetermined center energy sum is 1/1000 of the center energy sum.
 16. AFMCW radar system according to claim 12, wherein the processingcircuitry is configured to: classify the object/UAV track as non-realUAV track when the determined outer energy sum is below a predeterminedfraction of the determined total energy sum.
 17. A FMCW radar systemaccording to claim 13, wherein the processing circuitry is configuredto: classify the object/UAV track as a non-UAV or large UAV track whenthe determined total energy sum is above a predetermined maximum energyrepresenting a predetermined maximum radar cross-section, wherein thepredetermined maximum radar cross-section is 1 m².
 18. A FMCW radarsystem according to claim 12, wherein the processing circuitry isconfigured to: determine radial velocity boundaries for the centervelocity range, and determine radial velocity boundaries for the firstouter velocity range including negative radial velocity signals andradial velocity boundaries for the second outer velocity range includingpositive radial velocity signals, said determination of the velocityboundaries of the first and second velocity ranges being based on theradial velocity boundaries for the center velocity range and the totalobserved velocity range.
 19. A FMCW radar system according to claim 12,wherein the processing circuitry is configured to: determine radialvelocity boundaries for the center velocity range based on variations inobserved energy levels of returned radar signals as a function of radialvelocity.
 20. A FMCW radar system according to claim 19, wherein theprocessing circuitry is configured to: determine a decrease in observedenergy level to a local minimum on both sides of the center velocity ofthe observed velocity range, determine the radial velocity boundariesfor the center velocity range as the radial velocities for which theobserved energy level on both sides of the center velocity has increasedby a predetermined factor from the observed local minima.
 21. A FMCWradar system according to claim 12, wherein the processing circuitry isconfigured to: generate full data type radar plots based on grouping ofneighboring hit range cells within one or more image lines of a fullcircular radar image having matching range, azimuth and radial velocitydata.